Nova Southeastern University
Many academic courses were introduced within the medium of distance education. A few empirical studies have examined the variables and challenges that may be encountered. Such variables may include class size, gender, grade levels, and lab inclusion. This study seeks to analyze distance education chemistry (DEC) by using a meta-analysis approach. The researcher’s intent is to reveal quantitative findings that either support or refute the previously debated theory that DEC is equivalent and as beneficial to traditional chemistry courses.
By using keywords such as “distance education,” “online chemistry,” “distance education chemistry,” “Internet chemistry,” and “college online science,” a thorough search will be conducted using major educational library databases like WilsonWeb, Education Resources Information Center (ERIC), and Applied Dissertations. Once the peer-reviewed journal articles, magazine articles, and published and non-published dissertation reports have been amassed, they will be reviewed in depth. Studies that do not the fit the criterion of comparative analysis will be eliminated, since meta-analysis seeks to analyze results of statistical quantitative data featuring the studies of Glenn, 2001; Russell, 1999 & Vroeginday, 2005.
All data meeting inclusion criteria will be entered into the Comprehensive Meta-Analysis (CMA) software. CMA was developed in collaboration with many of the recognized experts in the field of meta-analysis, both in the U.S. and in the UK. It includes a wide array of sophisticated options for data entry, analysis, and display (Meta-Analysis Software Comparison, 2006). An effect size (Cohen’s d), correlation coefficients, and other representative ratios will be derived. Effect size (ES) affords the researcher the opportunity to compare variables across studies. In essence, ES simplifies the process of comparing variables within many studies.
Chapter 1: Introduction
Distance Education is transforming academic communities utilizing technological advanced and innovative methods to modernize traditional distance learning. Traditional classroom learning has given way to distance education (DE), an innovative alternative to traditional learning that is transforming the educational landscape. Distance education (DE) is any instructional education that transpires via technological means More technically, DE is instruction/education that is delivered to students who are not physically “on-site.”. DE began before modern technology. Ancient biblical writings evidence instruction to early Christians through letters. Mail, television, and radio were utilized prior to contemporary innovative technology. The Internet has made DE much more convenient.
Computer technology has resulted in exponential growth in the field of distance learning (Patterson, 2000). This development has stemmed largely from the fact that no considerable discrepancies between distance education, or online learning, and traditional classroom learning have been found. Current DE pedagogy has proven itself to be commensurate with traditional face-to-face (F2F) learning. In fact, many students believe that online learning is more efficient and beneficial than the usual modes of learning
DE has been proven to be equivalent to?and in many cases more ideal than?traditional “face-to-face” learning, provided that the necessary variables meet the students’ needs. Ajda Kahveci, an author that has conducted extensive studies on Distance Learning, asserts “It is apparent in most of the studies that distance chemistry learners are not disadvantaged compared with their on-site counterparts” (Kahveci, 2003). Students today are attracted in large numbers to DE because it affords the convenience of taking classes that fulfill degree requirements from home. Students appreciate the fact that the stress of commute is eliminated.
Many major educational institutions have adopted online learning. In time, more institutions are expected to follow. Increase in online education stems not only from urgent demand, but from student retention rates and increased faculty effectiveness. DE has capitalized on the avenues offered by the Internet and has manifested itself in various formats, such as eCollege, virtual schools/learning, cyber learning, Web-based instruction, virtual labs, and synchronous online lectures/classes. Some institutions have created technological vehicles in which students are able to resume location at any point in the lecture when they have misunderstood or missed a point. Patterson and Kahveci, both agree that access to audio files of lectures and presentations, online, is undeniably powerful and a defining resource for the modern student
Many of the studies that have been performed show no significant differences in the learning and achievement outcomes between the face-to-face and online learning variables:
According to the analysis of the data in this study no significant differences were found between the students who completed the political science courses via distance learning and those who completed political science courses on campus (Glenn, 2001).
Hauck (2006) quotes Russell’s research, which found no significant differences between the effectiveness of distance education and face-to-face classes in 355 comparison studies. Russell’s studies were concerned primarily with students in fashion merchandizing courses, but are applicable to other course work as well.
Vroeginday (2005) also reports that many studies suggest there is no significant difference in course assessments and outcomes between traditional and distance learners (Russell, 1999), and that the instructional strategy makes the difference, not the medium by which it is transmitted (Morrison, 2001). Vroeginday’s study analyzed such variables as learner attrition, gender, marital status, age, number of children, age of the youngest child, employment status, income, highest educational level, and computer-related proficiency. Although there were differences related to the preceding variables, no significant difference in learner outcomes were found between the face-to-face learners and the online learners. In fact, the results of the study indicated that online learners actually performed significantly better on the final exam than the traditional learners; however, there were no significant differences observed with respect to overall course scores (Vroeginday, 2005).
Although online science-based courses face some challenges, they are attracting attention and are increasingly gaining acceptance. The problem of how to incorporate essential hands-on laboratory experience is slowly but surely being eliminated. Regarding graduate science education and laboratory activities, technological tools now exist online that can enhance the student’s learning experience sufficiently until a significant real-time laboratory component can be incorporated into the graduate science degree program (Spevak, 2004).
However, the literature fails, for the most part, to specify if the studies of distance learning in the sciences have considered certain variables, such as whether or not the course of study was potentially dangerous, whether or not it involved a laboratory component, and other topics of vital importance to teachers and students of chemistry. Many recent studies examine various aspects of problems involved in providing Internet instruction in classes requiring laboratory work (Burke & Greenbowe, 1998; Hjorth-Gustin, 2004; Kennepohl & Last, 2000; Kimbrough & Reeves, 2004; Madore, 1998; Patterson, 2000; Rice, 2004). To date, these studies have not been compared and contrasted. The meta-analysis of the extant research will include examination of the many important variables that have been studied, such as age, gender, attrition, learner achievement, score outcomes, and retention rates, to name a few. The study will also include analysis of the rigors of the various studies.
Nature of the Problem
The purpose of the proposed research will be to provide a meta-analysis of the published research comparing chemistry instruction in classroom settings with distance education chemistry (DEC) to determine the advantages and disadvantages of each, and to make recommendations for current DEC program construction.
Distance learning programs have an advantage over traditional brick-and-mortar-based classrooms in that they can reach students all over the world. In fact, over the next few years, more than 2.3 million U.S. students will be enrolled in distance-learning courses, according to the Directory of Schools Distance Learning Programs (2006). In the technological age of the 21st century, programs need to include information that is immediate, current, and easily accessible at all levels. This becomes a challenge when dealing with the hard sciences. Most universities require at least one laboratory science course, and all health-related majors require at least one semester of laboratory-based general chemistry. Educators face a problem in providing distance learners with the laboratory experience instruction required for the courses (Reeves & Kimbrough, 2004). Making a laboratory science course accessible to distance learners requires eliminating certain barriers, a challenge that must be met if undergraduate degree programs for distance learners are to be successful.
There are a few potential obstacles that can stifle the development and growth of DEC. Some of these potential problems include, but are not limited to, simulation of the traditional lab adequate to provide the necessary experience and attributes gained in the classroom, absence of group collaboration, and a lack of hands-on experience. According to Forinash & Wisman, 2001, though DEC labs have seen some growth in the past six years, incorporating science labs still poses a challenge. However, there are options available. The writer is a chemistry teacher and proposes the following three alternatives: 1) Chemistry kits with prescribed labs that are hazard free and safe enough to be performed within the home (students must sign a disclaimer); 2) software programs with point-and-click labs (recommended for post-graduate or upper level undergraduate students who are very experienced with “hands-on” chemistry; and 3) students attend an on-site lab that is not necessarily F2F or main campus-based.
Background and Significance of the Problem
Some students’ performance improves greatly outside of the classroom setting, according to Reeves and Kimbrough (2004).They feel less academically hindered, less rigor, and more liberated when there is less intrusion from either distraction by their peers or teacher/student indifference. If it is shown that DEC classes are effective and of high quality, this may become a popular remedy for both the shortages of teachers in scientific studies, as well as attracting students who prefer this type of educational experience (Bernard, R. M., Abrami, P. C., Lou, Y., Borokhovski, E., Wade, A. Wozney, L. et al., 2004).
Because advanced science courses such as Honors and Advanced Placement classes, biology, chemistry, and physics have very low student-teacher ratios, they are often cancelled because too few students enroll.
Distance education programs can fill a great unmet need, but the programs must provide the same level of knowledge as those taught in the regular classroom. However, those who design courses must look to the research for “best practices;” little work has been done to synthesize current, valid research results on the topic. The meta-analysis will provide information to those who must design distance programs in the sciences where a laboratory component is necessary.
Florida, like many other locations, is experiencing a shortage of teachers, especially in the sciences. The shortage stems from the fact that fewer teachers are entering the field. According to the Florida Teacher Recruitment Campaign (2000), retirement and resignation, as well as the class-size reduction amendment, have created a drastic increase in the need for teachers; math and science teachers are in greatest demand. The Florida Department of Education recently estimated that 2,308 math and 1,938 science teachers would be needed by the fall of 2006.
The research base must be examined, since some analysts have been skeptical of distance education programs that omit direct interaction. A meta-analysis of the research comparing distance to traditional learning models may reveal that interaction is possible, or is perhaps over-rated. This study will help determine what types of learning models have been shown to work well.
According to Madore (1998), secondary schools with very few students and a small range of science classes could profit from distance learning options. Consequently, if DEC is available and effective, schools facing economic challenges in hiring teachers for such low teacher-student ratio classes may benefit. These schools may not be offering certain science courses. It is important, then, to determine whether DEC will meet the needs of students who prefer this type of instruction?those who have difficulty finding an available class experience, those who live far away from the best schools, and those who are home-schooled, as well as students in areas where the school curriculum tends to be insufficient. Several research questions need to be answered to determine whether attraction of?and effectiveness of?DEC programs can be shown, through meta-analysis, to hold potential to meet these and other unmet needs.
Most of the research questions will refer to variables reported in the literature. While many research questions will arise from the literature review in an iterative process, some questions the study might help address include:
1. What empirical evidence exists in the literature about the differences between course content of DEC classes and those of traditional chemistry classes?
2. When an empirical comparison is made of DEC to in-class instruction, do major differences exist between course content of DEC classes and traditional chemistry classes?
3. Does the research support or refute the perception of academic effectiveness of DEC for experimental and control groups?
Chapter 2: Review of Related Literature
Since the advent of distance education via technology, much debate has transpired between distance education technology advocates and those who believe distance education is a threat to traditional methods of learning. An ideal analysis of distance education vs. the usual routes takes an intrinsic and most relevant variable into consideration. The variable in question is the attitudes of faculty members toward DE. Many attitudes have surfaced among faculty members. This review seeks to describe the attitudes of faculty members of prominent learning institutions toward distance education and the benefits of traditional classroom learning vs. distance education learning. Many institutions grappled with the idea of distance education until they began reaping its benefits. Investigation into the attitudes of faculty members toward distance education may reveal hidden reasons for comparatively slow adoption by higher education institutions .
The writer conducted an extensive search for dissertations focusing on the attitudes of faculty members of institutions of higher learning toward distance education. Although faculty members’ attitudes toward distance education are a fairly broad topic, the writer believed it was best to include as many variables as possible. Such variables ranged from types of academic institutions, age range of faculty members, gender, and computer-mediated distance education to localized research vs. national research. After amassing approximately twenty dissertations and journal articles from Nova Research Library, the writer browsed the abstracts and content areas to determine if the various variables relevant to faculty attitudes were included. Some articles and dissertations were eliminated based on the fact that they focused exclusively on students’ attitudes or attitudes of non-faculty members. The initial motivating factor to explore faculty attitudes towards distance education stemmed from the writer wanting to investigate the general attitude toward distance education via technology; however, faculty attitudes toward distance education is more reliable, since first-hand variables are at work with faculty more so than with other groups.
Numerous studies have addressed faculty attitudes toward distance education technology (Bender, 2002; Clark, 1992; O’Quinn, 2002; Smith, 2004). Of these studies,it is the Clark study which is most comprehension. The purpose of the Clark study was to describe and analyze the attitudes of faculty members at public U.S. institutions of higher education towards college-credit distance education (Clark, 1992). Most studies since the Clark study make reference to Clark as a classic and national landmark study (Awalt, 2003; Challis, 1998; Reasons, 1999; Ross, 1997). Clark reported that “no previous studies were found in the literature in which an attempt was made to determine overall U.S. college and university faculty attitudes toward the concept of distance education or the media and methods commonly used in its provision” . Topics discussed in this review include negative and positive attitudes of faculty toward distance education via technology, reasons for the differences in attitudes, how attitudes have changed, the influence these attitudes have on what faculty do about their distance education programs, the attempts that have been made to change faculty attitudes, differences and similarities of faculty distance education studies, gaps in studies or areas that need more research (limitations of studies), and specific directions for future research.
Taylor & Todd (1995) stated that an individual’s behavioral intention is determined by his attitude toward the innovation’s perceived ease of use and awareness of its usefulness. Two schools of thought governing attitudes have emerged and influenced prevailing thoughts. With the emergence of the theme of a brick-and-mortar mentality, the opposite theme also surfaced?a theme my colleague and I call brick-and -click mentality—a mindset that promotes the use of technology in higher education . Faculty attitudes are governed by two paradigms: negative and positive. All studies utilized expressed both positive and negative faculty attitudes toward distance education computer-mediated technology. For example, O’Quinn (2002) states that while faculties were divided in their views towards DE, most were positive, and 69% of division chairs were positive with regards to DE. O’Quinn, after an intensive 334 faculties study, explains that over half of the educational professionals, at a baccalaureate level, interviewed believed that distance learning was a positive experience. In comparison, only a fourth felt that distance education was not helpful and held a negative attitude. At a masters and doctoral level, the majority of respondents believed that distance education was a helpful tool and held a positive attitude (O’Quinn, p. X).
Challis (1998) cited Kirby (1988), who mentions that on one hand, the traditionalists often view distance education as the ultimate erosion of academic standards, whereas on the other hand, distance education advocates see opposition to their cause as obstructionism and academic protectionism. Challis also reported that studies on positive attitudes toward telecourses indicated that these feelings were due to the belief that the medium increased enrollment and created additional opportunities for nontraditional students, as well as provided “alternative means of filling required courses.” Iken (2000), in a dissertation section entitled “Faculty Attitudes toward Distance Education,” reports striking contrasts in faculty attitudes toward distance education. One analyst claims that DE is one of the most dramatic technology-based innovations in education, while another states that distance learning often provides only an illusion of learning.
There are many reasons why faculty attitudes vary. Reasons for differences in faculty attitudes are explored in Clark’s (1992) research because his research was national, and he made sure there were minimal differences, if any, among the independent variables. Clark’s findings suggest considerable variations in the attitudes of faculty members of public higher education institutions toward distance education? in general and specific academic settings, via specific media/methods, based on previous experience with instructional media and distance education (DE), familiarity with DE, gender, and institutional classification. Faculties surveyed in comparable institutions were fairly similar in terms of age, sex, tenure, and academic rank, as reported by the National Center for Education Statistics (NCES). NCES explains that the insignificant negative attitudes toward distance learning were exclusively found within fine arts and positive attitudes were held in other content areas including health professionals (NCES, p. 68).
An extensive and up-to-date study analyzing the perceptions of faculty members of nine Seventh Day Adventist colleges and universities yielded results based on faculty gender and other faculty variables of online distance education benchmarks .
Smith’s study revealed significant differences between male and female perceptions of course development benchmarks, teaching/learning benchmarks, course structure benchmarks, student support benchmarks, and evaluation and assessment benchmarks. Women’s scores for the means on all benchmarks showed they had much more positive attitudes than men. and reveal similar gender patterns. Clark found that women at two-year institutions were significantly more positive than men. did not show any significant differences in attitudes toward distance education related to gender or ethnicity; however there were differences in knowledge and use of instructional technologies related to the respondent’s age and number of years teaching . Data from a faculty attitude questionnaire revealed gender and other faculty attributes had no significant impact on faculty perceptions. This was more than likely due to the fact that the study was fairly limited in its scope to the University of Nevada, Las Vegas. Faculty attitudes toward technology-based distance education vary across a continuum, and are not impacted by age, gender, tenure status, number of years teaching at UNLV, or even the total number of years teaching in a university environment.
Four reasons given for differences in faculty attitudes toward distance education were: 1) computer anxiety level; 2) technological experience; 3) peer influence; and 4) discipline types. For both study groups, computer anxiety accounted for a considerable proportion of variance regarding attitudes toward a transition to distance education, toward distance education’s impact on the respondent’s field, and toward distance education’s impact on higher education . The findings of Heath (1996), Lucy (1993), and Clark (1992) also indicated that knowledge and use of instructional technologies were positively correlated with more favorable attitudes toward distance education . As in many attitudes, the influence of peer pressure found its way into faculty attitudes toward online distance education. Obviously, peer influence is an invisible variable in many studies. Clark explains that many educators and faculty members have little personal experience with distance learning and their impressions of distance learning are based on what their peers have expressed to them, or literature on the subject – not personal experience (Clark, 1992).
It has been the writer’s experience in conversing with various professors and teachers, as well as in analyzing course offerings within Online distance education, that education and business programs receive the most support. Black’s (1998) studies reported that faculty in the hard and pure disciplines were significantly less supportive of distance education than those in the soft and applied disciplines. The hard, pure, natural science grouping was the least supportive overall . Of course, contemporary science requires a hands-on approach and will continue to attract much debate regarding its availability in Online distance learning programs.
As the public becomes more aware of the benefits of technology and the conveniences provided by Online distance education, people become more receptive. There are now less negative attitudes toward distance education technology and more positive attitudes. Previously existing systems were not in place to accommodate today’s widespread and conventional use of computer technology; therefore, faculty and non- faculty could not make intelligent and well-informed decisions concerning long-term outcomes of distance education technology. Studies like Challis’ (1998) confirm the lack of information regarding distance education. The study also determined that the Utah faculty needs to be furnished with information concerning the effectiveness and quality of distance education, cites Parer (1988), who stated, “Although they indicated that participating faculty perceived distance education to be a responsible academic pursuit, the faculty believed that distance education lacks the prestige among colleagues in traditional settings” (p.68)
Earlier attitudes were unsupported by empirical evidence. Research emerging during the 1990s to 2000 and beyond confirmed similar? as well as greater ?benefits from distance education technology (Clark, 1992; Heath, 1996; Ross, 1997). The benefits of one’s sense of achievement and personal job competitiveness resulting from obtaining a distance education degree are equivalent to those benefits resulting from obtaining degrees via traditional face-to-face routes. Allen & Seaman (2006) confirm the fact that by an increasing margin, most Chief Academic Officers believe that the quality of online instruction is equal to or superior than that of face-to-face learning. There was also some uncertainty as to whether distance education could meet the needs of education. cites Black (1998), who reports that one of the major challenges facing the development and expansion of distance education is faculty skepticism and resistance concerning course quality. The prevailing thought was that distance education could satisfy the needs of business or education degrees. The faculty stressed the need students have for face-to-face interaction with professors and with their peers, but weren’t sure distance education methods could deliver the needed interaction . It is now a known fact that distance education accommodates nearly all available face-to-face programs. More than 96 percent of the very largest institutions (more than 15,000 total enrollment) have some offeringsonline, which is more than double the rate observed for the smallest institutions . The Internet article cites two major evidences for changes in the perceptions of quality of offerings: 1) In 2003, more than half of academic leaders measured online learning commensurate with F2F or superseding F2F outcomes; and 2) There was a 4.8% increase between 2003-2006 among those who rated F2F equivalent or superior to traditional instruction or education.
Another reason that distance education was slow in gaining acceptance was faculty perception that if they participated in or supported DE, their jobs and security would be at stake. Several studies (Heinich, 1985; Lewis & Will, 1990; Shrock, 1985) suggest that some faculty perceive technology-based distance education instruction as a threat to the normalcy and reliability of their position .
The impact on faculty attitudes is one of the single most influential factors in determining what universities do about their online distance education programs. Faculty members and departments which are supportive of distance learning are more likely to have successful distance learning programs. Studies such as Challis (1998), Clark (1992), Dillon & Walsh (1993), and Stinehart (1987) report that the attitude of the leadership? i.e., the department chairs or college deans?greatly impacted, either negatively or positively, the attitudes of faculty members . The influence of faculty attitude on the growth of online distance education is also most significant when one considers the fact that faculties are fully aware of the pros and cons regarding online distance education. Regardless of the positive or negatively attitudes held by faculty members, it is the administration’s responsibility to recognized that peers may be influencing these attitudes and they should support faculty in gaining personal experience and their own opinion about distance learning (Source, p. 31).
As is common in much contemporary research, there are gaps in the studies or areas that need more research. Many gaps concerning faculty attitudes and the impact they have on distanced education technology have been filled; one need only compare the years 1998 through 2006. Much more research remains to be done concerning the basis of faculty attitudes and the role they play in the diffusion process of distance education in higher education institutions (Betts, 1998; Challis, 1998; Clark, 1992; Dillon ; Walsh, 1992; LaRose, 1986; Lindquist, 1978; Mani, 1988; McNeil, 1990). Since 1998, many studies (Awalt, 2003; Bender, 2002; Iken, 2000; O’Quinn, 2002; Reasons, 1999; Schoats, 2002; Smith, 2004) have been done which shed much greater light on distance education faculty attitudes.
Gaps relating to gender are found in the studies of Clark (1992) and Smith (2004). Although Smith (2004) did not intend to research gender influence on faculty attitudes within distance education, she uncovered some expected findings. Smith remarked that reasons for differences in faculty attitudes based on gender were unsure. Reasons for the gender differences are speculative and may be explained by traditionally formed gender roles of women being more nurturing, while men are more authoritative (Smith, 2004). This area could serve as a springboard for further research.
Further limitations exist in much of the research concerning faculty attitudes toward distance education. Although many studies state findings and results of their research, some offer penned delimitations, limitations, and sections outlining and detailing reasons why their work might contain biased results. Wang, MacArthur, and Crosby (2003) clearly stated that since the participants of the survey were not mandated to take the survey, those who responded may have had stronger opinions about the subject that motivated them to respond. Clark (1992) commented that “many of the studies on faculty attitudes toward college credit distance education or related topics found in the literature are not generalizable because they are based on research conducted at no more than a few institutions of higher education” (p.9). In addition, many studies fall into the category of being fairly limited in their scope. Studies (GilChrist, 1997; Montgomery, 1998; Reasons, 1999; Ross, 1997; Smith, 2004; Wang, MacArthur, ; Crosby, 2003) offered for faculty attitudes toward distance education tended to focus on a localized setting rather than a more national scale (Clark, 1992).
Further studies documenting limitations include Iken (2000), Clark (1992), Smith (2004), and O’Quinn (2002). Iken (2000) remarked that because of the precise nature of the findings, they may only be generalizable to schools with similar descriptive profiles. Iken further stated that because the research design utilized time-bound, static survey methods which generated cross-sectional data, the generalizability of the findings is limited. Smith (2004) clearly documents limitations by admitting that names and institutions are attached to the participants’ survey information; they may provide information to improve the image of their institution or the position they hold in the institution. Furthermore, Smith stated that the participants in her study were limited to those chosen from nine Adventist institutions of higher education actively teaching Internet-based courses at the time of data collection. O’Quinn (2002) expressed limitations in generalization. The data gathered from this study is only generalizable to community colleges located in large metropolitan areas with a population of distanced faculty that is small relative to the faculty who only teach classroom courses (O’Quinn, 2002).
Although much research was carried out since Clark’s research in individual institutions, none extended to the level recommended by Clark GilChrist (1997) remarked that the St. Cloud State University case study was narrow in scope and that longitudinal studies could have provided better results. A few studies were limited due to insufficient data. Montgomery (1998) remarked that additional data concerning the positive and negative aspects of each model factor is needed to better define the differences existing in faculty attitudes and to refine the Attitudinal Differences Model. A study by Sumral (2002) stated that because of the low response rate of 11%, the researcher is unable to generalize the study beyond the respondents.
Attitudes vacillate and gravitate from one minute to the next, making attitudes toward distance education a very complex issue to investigate. As technologies appear, disappear, and reappear, attitudes tend to be reflective of one’s exposure to technology and its facilitation of education. Additional evidence in support of the limitations which are based on attitude was observed in Bender (2002), who remarked that simply taking the pretest may change a person’s attitude (Solomon, 1949).
This review was very extensive in its scope by analyzing research and major dissertations that have been done to date concerning faculty attitudes toward the various aspects of distance education and related variables. Presently, the most powerful study performed is that of Clark (1992). Clark’s study was more generalizable since it employed a nationwide survey of faculty members, unlike other studies which merely focused on a specific college or university. Faculty members possess both negative and positive attitudes toward distance education. Attitudes are reflective of exposure, discipline, era of distance education technological development, age, gender, and varying demographics. Furthermore, bias is often introduced into much of the research. Faculty members, in an attempt to bolster the image of their institution, often give false impressions.
This study, although not designed to reveal the pros and cons of distance education, unexpectedly reveals the advantages of distance education. Such advantages unintentionally surfaced due to faculty members’ revelations concerning their own attitudes toward distance education. Another unintended issue that came to light included the fact that faculty members’ attitudes toward distance education have changed since 1992. Faculty members have overcome the anxiety associated with computer use, and therefore are more acclimated to the workings of distance education technology.
The review fulfilled its purpose and intended objective. Rather than conclude that faculty attitudes are more positive or more negative, focus was placed on the fact that there are many subjective variables which influence faculty members’ perceptions of distance education. The lack of generalization was stressed to a great extent. Most of the researchers recommended more generalizable research; however, generalization may not be easily facilitated. In addition to the variables viewed in this writing, more variables¾ such as types of computer applications being used for distance education, new and various disciplines, subject areas being taught, and how institutions have responded to negative faculty attitudes toward distance education¾are possible topics within the “attitude toward distance educational technology” domain that require further research.
While many research critics express skepticism concerning the validity of circumventing traditional in-class taught chemistry courses, other research studies reveal online distance education chemistry serves as well as traditional modes of chemistry instruction (Hjorth-Gustin, 2004; Kennepohl, ; Last, 2000; Kimbrough ; Reeves, 2004; Rice, 2004). Numerous research studies include findings applicable to distance education chemistry instruction at all academic levels.
For the meta-analysis of the research findings, studies will be divided into two major categories: 1) comparative studies between traditional in-class education and online-distance education format, and 2) sole focus research on the effectiveness of distance education chemistry.
The researcher has identified a classic study by Bayraktar (2000) that contains 42 studies, including biology, chemistry (13 studies), physics, and general science, that are traditional computer-assisted instruction (CAI) science programs. Including these studies, among many others, will serve as a good analysis of the effect of instructional technology on chemistry education and covariate analysis.
During the past 2 decades, education and learning pedagogy have transformed and manifested themselves into innovative and novel schools. The advent of the Internet has provided a foundation on which to build an increasing number of vehicles for learning and instruction. To date, a few of these vehicles are eCollege, virtual schools, Cyber learning, Web-based instruction, virtual labs, and synchronous/asynchronous classes. DE has been active since the early 1900s. Radio, TV, mail, and satellite delivery have been outmoded. From the early 1990s, online education has increased the number of available mediums for teaching and learning. Many educational institutions that have delayed participating in online instruction have now hopped on the bandwagon, having realized the benefits and conveniences they may provide to students. Some of the benefits provided by online universities and web-based institutions include the elimination of commute and the face-to-face environment, the convenience of attending classes at one’s leisure, and the ability to access course materials during personal “downtime”. The demand for online learning has become so great that in the near future, all educational institutions (k-12 and beyond) will need to make ajustments for incorporating online learning as part of the programs and courses they offer.a. The writer is currently pursuing an advanced degree utilizing Nova Southeastern’s well-developed and renowned online degree programs. Many students who would not have considered entering academia have returned to school by taking advantage of web-based learning. Distance learning has also lead to a new avenue of financial funding for public colleges which have had their governmental support cut. Internet courses decrease the need for campus residence halls and classroom space and therefore the cost (Maquire, 2005).
There are, however, some potential challenges faced by online learning. With time, these challenges will be eliminated as technological resources are upgraded and become more advanced. . Many skeptics and critics alike believe it is impossible to simulate the classroom environment. Hence, they believe that online learning is not beneficially equivalent to face-to-face learning. The studies, however, have proven that provided the instruction is well-structured in an online learning environment, student achievement and success is commensurate with traditional learning, and in many cases surpasses traditional routes of learning. Students who have gone through web-based instruction have concluded that they are more satisfied with being able to access course material at their own leisure, and that they felt less stressed.
Other students believe online learning is not suited to their needs, since they are unable to remain confined to a computer for extended periods of time. The social element for these students is also an intrinsic part of learning. Some institutions make their programs available in what are known as blended models. Blended models give students the option of taking some programs on campus.
Online education is not the solution to all of education’s problems. However, distance learning can provide a viable solution to many of the concerns facing current educational communities including low government support, low graduation rates, and the need to be technological advanced in modern societies. The necessity of distance education is supported by more and more employers who are accepting online degrees¾providing the school is accredited.
One major problem facing online education is how to offer the practical portions of the classroom online. While it is true that students cannot hold integral apparatus present in many classrooms, there are a number of viable solutions that are applicable to courses where practice and hands-on are a necessity. In advanced courses, students are expected to have basic coursework and laboratory experience. Subsequently, they may gain further experience in the online environment through simulated labs that utilize software to mimic the actual equipment and labs required for successful experience in the real world.
Some studies indicate that online Distance Education Chemistry (DEC) instruction is not only synonymous in its value with the traditional format, but more efficient and effective (Clark, 1992; Kimbrough ; Reeves, 2004). Several researchers have performed studies that reveal equal chances of success using revolutionary external-classroom modes of chemistry instruction (Hjorth-Gustin, 2004; Liu, 1996; Kahveci, 2003; Rice, 1996). Furthermore, effectiveness studies of distance education chemistry were found in the work of Gorsky, Caspi, and Tuvi-Arad (2004), Burke and Greenbowe (1998), Patterson (2000), and Kennephol and Last (2000).
Another study is an analysis of a telegraphic chemistry course. Madore (1998) analyzed students’ perceptions of a telecommunication telegraphic distance chemistry course. The 26 students enrolled in the DEC course submitted their perceptions via instruments such as measurement tests, diaries, and telephone interviews. Classroom students felt that teacher availability and direct contact was necessary to ensure their academic success, while distance students felt that working independently without teacher supervision gave them a sense of maturity (Madore, 1998). Clearly, the research is inconsistent.
Although studies address major issues of validity and reliability concerning the effectiveness of distance education chemistry, few explain how these data were gathered. In one study, in which researchers asked if certain students should be selected for DEC, the question did not answer the problem addressed here, and the research results failed to give suggestions for a more realistic and ideal program.
Chapter 3: Methodology
A meta-analysis is a search for relevant primary source documents on a topic under analysis. In a meta-analysis, the researcher must not rely on abstracts and secondary source reviews, as in conventional literature reviews. Primary source documents must be examined to determine issues of validity and reliability, to compute effect sizes, and to code relevant features of the studies. It may also be necessary to contact the researchers to determine information that may be missing from the research report (Gall et al., 1963/2003).
Meta-analysis is a statistical procedure that can be used to analyze trends in the magnitude of effects observed in a set of quantitative research studies involving the same research problem. The analysis is an attempt by the analyst to determine what trends and patterns are important, usually in an emerging field. In a typical meta-analysis, reports of all available impact assessment studies of a particular intervention or type of program are first collected.
In the meta-analysis, data are combined from multiple studies. When the treatment effect (or effect size) is consistent from one study to the next, meta-analysis can be used to identify this common effect. When the effect varies from one study to the next, meta-analysis may be used to identify the reason for the variation (Borenstein, 2005). That is, other variables to be studied can be added whenever the meta-analysis suggests that another variable may be responsible for some of the variance.
Bernard et al. (2004) provided several reasons for using this type of research. The researchers claimed that the most relevant reasons for meta-analysis are: 1) that it maximizes external validity or generalization by addressing a large collection of studies; 2) that it improves statistical power when a large number of studies are analyzed; and 3) that it allows new studies to be added as they become available, or allows studies to be deleted as they are judged to be anomalous. A quantitative synthesis of relevant variables will be presented.
In this case, the analysis will determine whether there is evidence in the literature that DEC is sufficiently effective and economical so that it can be used to help alleviate problems in the field, especially the paucity of instructors and the importance of student perception. Since the 1970s, meta-analysis has been the most widely used method for synthesizing the statistical results of a group of studies on the same research problem (Gall et al., 1963/2003).
Many research articles and studies will be judged and evaluated before inclusion in the study. Data sources and electronic media from which previous research papers, articles, and dissertations have already been drawn include the following: Education Resources Information Center (ERIC), Dissertation Abstracts International, Journal of Chemical Education, ProQuest, WilsonWeb, and web search engines such as Google and Yahoo. After assembling the necessary literature, extensive reading will assist in deciding which literature will meet the necessary criterion for research.
A major variable for this study will be the influence of faculty attitudes on DE.
The studies’ approaches and methods used are replete with Likert surveys and questionnaires. Qualitative studies on faculty attitudes are found in the works of Schoats (2002) and GilChrist (1997). While other research work employs a quantitative method, as found in Wang, MacArthur, and Crosby (2003), one study by Smith (2004) employed both quantitative and qualitative methods. The table below reveals the names, dates, methods (quantitative, qualitative, or both), major research techniques employed for each study, and the study’s higher institution location.
Sources of Data
The research articles included in the meta-analysis must refer to a population to which the results can be generalized. School data are highly regionalized. For the purposes of this research, any study on DEC in high school chemistry, as well as undergrad and graduate school academic populations, will be utilized. When an empirical comparison is made of DEC to in-class instruction, differences that exist between course content of DEC classes and traditional chemistry classes will be examined.
Studies will be included if they specify the distance from the instructor, when outcome data are presented, when the perception of academic effectiveness of DEC for both experimental and control groups is given, and when the data address at least one achievement, attitude, or retention outcome measures, and comparable data between control and study groups.
Research on the subject performed from 1996 to the present will be analyzed to determine similarities and differences in outcomes between the traditional and distance educational models. The study design will be similar to that adopted for a meta-analysis in the work of Bernard, Abrami, Lou and Borokhovski, et al. (2004). These researchers used a quasi-comparative approach to compare distance education delivery and classroom courses. The work was general in that empirical studies since 1985 from major research journals were synthesized into a research model in order to examine student retention, attitude, and achievement in distance delivery models and the general education classrooms. The research model they designed for use in the proposed study will involve examination of the research done in the last five years to determine whether student attitudes, retention rates, or achievement outcomes are different for students who receive chemistry instruction in the traditional setting compared with students enrolled in DEC classes. The study, then, is designed to review the literature about the effects of on-line instruction on student attitudes, retention rates, and achievement outcomes.
Using DEC terms as keywords, databases and libraries will be searched for relevant research studies. The databases include ERIC, Social Science Citation Index (SSCI), PsychINFO, Education Abstracts, and Digital Dissertation Index. Other sources are PROQUEST, Journal of Research in Science Teaching, Journal of Computers in Mathematics and Science Teaching, Computers in the Schools, Journal of Research on Technology in Education, Science Education, and Journal of Chemical Education.
The exhaustive examination of all research studies on DEC will, as noted, provide specific parameters, such as whether the program contained a laboratory component, the academic year (secondary or college) of the students, the absence or presence of certain components such as presence of faculty in a chat room, the availability of a chemistry lab, substitutions available for safer experiments, and any other variable found to be central to the studies. As many studies as possible will be examined. The researcher will include in the study all variables that fit the purposes of the study. The studies will be eliminated based on whether or not they possess enough data to produce effect sizes.
Each of the studies will be examined and a list of study variables will be organized to include all the ones upon which findings are reported. Next, the bibliographies of these studies will be examined for other studies of interest. All of the studies will be thoroughly examined, studied, and assessed for inclusion as variables of interest, which will then be encoded and entered in the Comprehensive Meta-Analysis (CMA) Computer Software 2.0 database, a specialized meta-analytical software program. Data that will be included in this analysis will consist of a reliability score, a generalizability score, and demographic data, such as ages, gender, ethnicity, and home location of participants (Borenstein, 2005).
Method of Analysis/ Statistical Software
Borenstein (2005) has designed computer software, Comprehensive Meta-Analysis (CMA) Version 2.0, to assist in conducting meta analyses. The program effects on selected outcomes are encoded as effect sizes using an effect size statistic. Other descriptive information about the evaluation methods, program participants, and nature of the intervention is also recorded. In this study, a meta-analysis will be performed on programs of study in chemistry.
Planned CMA Protocol
Meta Analysis 2.0 interface mimics Microsoft Excel except that it contains many parameters for statistical entries relative to meta analysis. By default, the first column is designed for study names, followed by another for effect size data. Odds ratio, log odds ratio, and standard error are displayed. The researcher has the option of setting the program to display other indices such risk ratios, risk differences, standard deviation in means, Hedgers Q, difference in means, standard paired difference, correlations, Fisher’s Z, rate ratio, Pearson’s r correlation, Cohen’s d, etc. Once all the necessary studies’ data are entered, a launch analysis module button is depressed.
Other features of CMA include analysis of a single removed study or cumulative analysis of all or any given select set of studies. CMA allows display of formulas for calculating coefficients, standard deviations, and means. The researcher will display all such formulas (e.g., formulas for computing effect sizes and forest plots). All effect sizes will be reported and analytically interpreted.
Possible Variables to Explore
CMA allows not only analysis of groups, but also of subgroups such as gender influence (male vs. female or both), academic levels, age groups, racial influence, specific chemistry topic content, instructor role, program length, school type, student setting, instructional styles, DEC medium, software technology type, same or different instructor, attrition rates, pre-test/post-test scores, study date, and publication type. These variables will become significant in the event radical effect sizes are encountered. Since an extensive library of literature on faculty attitudes toward DE was found, faculty attitudes will be incorporated as a single or number of different variables.
A publication bias (funnel plot) will be run to determine the effect of bias on the analysis. Absence of bias will display a symmetrical bell-shaped plot. Bias will show an asymmetrical funnel plot about the effect size.
This study will provide information to assist in analysis of the effectiveness and efficiency of DEC as compared to traditional delivery of chemistry classes. It is anticipated that this extensive search through the literature will provide information to guide the decision of whether or not such a program might be a viable alternative to solve problems of teacher shortage or student preference. Depending upon the research results, it may be fair to conclude that online DEC is or is not able to help fulfill an unmet need in science education. The results of this research will, at the very least, provide a heuristic for future studies and a useful source document for researchers.
Effect sizes must not significantly differ from zero. The researcher is hoping that most studies will be greater than or equal to zero, indicating the ideal nature of DEC programs. Effect sizes of approximately 0.2 are small. Effect sizes of 0.5 and 0.8 will indicate medium and large increases over the control group, respectively.
Timeline (subject to variation)
Months one to three: Conduct an extensive search utilizing search engines, electronic libraries, and catalogues for journal articles, dissertation research report PDF files, and related articles that provide quantitative data on traditional chemistry education versus online distance education chemistry outcomes.
Month four: Select viable research from the preliminary collection by the process of elimination. Some of the available research may be more qualitative, yielding descriptive data and not quantitative results; extensive reading of all derived research and quantifying preliminary data for entrance in database.
Month five: statistical analysis using meta-analysis spreadsheet database.
Month six: Graph construction and meta-analysis results presentation.
Many challenges exist in providing instruction in science education compared with teaching the social sciences. From an historic point of view, major chemists studied their hypotheses and theories utilizing laboratory work. There are more variables that need to be studied in providing chemistry instruction than in other distance learning subject areas. For instance, legal aspects need to be considered when working on chemicals outside of the laboratory. Students, if unsupervised, could combine chemicals in potentially dangerous ways. A challenge lies in determining how to offer the laboratory portion of the distance education coursework without risking injury to the student. However, the literature suggests several options and solutions, such as chemistry lab software designed to fulfill pre-designed chemical experiments, or even more simple¾utilization of safe, homemade substances for experiments. When comparing DEC and the usual methods of learning chemistry, achievements and learner outcomes are hinged not only on delivery, but on variables such as hands-on laboratory activities and the risks involved. It is appropriate and relevant to mention the pros and cons of online chemistry. First, it must be understood that online chemistry eliminates the dangers and hazards associated with traditional learning. In addition, the high costs of laboratory materials are eliminated. Students are also given the opportunity to work with technological equipment over the Internet and gain hands-on experience. Many chemistry labs are making use of what is known as Vernier software technology. Experience with Vernier tools may be gained over the Internet. Forinash and Wisman (2001) stated that by keeping the control of an experiment in the hands of the student, distance laboratories can achieve educational goals important in the traditional laboratory.
As a component of the meta-analysis, it may be useful and necessary to study the ways that others handle this and additional problems when considering these variables in the study. Study criteria, then, must arise iteratively during a thorough study of the literature base.
This and other similar studies are not to be relied upon as sole sources for evidence that DEC supersedes traditional chemistry in terms of effectiveness or that it is congruent. It may, however, along with other qualitative studies, provide ample evidence.
Distance education chemistry courses, like most distance education courses, are designed to meet the needs of the working student, as well as the needs of other students who may want to access a prestigious educational institution’s program from halfway around the world.
Abel, R. (2005). Achieving success internet challenges etc. The Alliance for Higher Education Competitiveness. Retrieved November 14, 2007 from http://www.a-hec.org/media/files/A-HEC_IsL0205_6.pdf
Allen, E., ; Seamann, J. (2006). Making the grade: online education in the united
states, 2006. Needham, Ma: The Sloan Consortium.
Bernard, R. M., Abrami, P. C., Lou, Y., Borokhovski, E., Wade, A. Wozney, L. et al. (2004). How does distance education compare with classroom instruction? a meta-analysis of the empirical literature. Review of Educational Research, 74(3), 379-439.
Borenstein, M. (2005). Comprehensive Meta-Analysis (Version 2.0) [Computer software]. Retrieved November 14, 2007 from http:// www.meta-analysis.com/ pages/ why_do.html
Brooks, D. W. (1995). Unpublished course information package.
Brooks, D. W. (1995). Face-to-face conversions by Daonian Liu.
Burke, K. A. ; Greenbowe, T. J. (1998). Collaborative distance education: the iowa chemistry education alliance. Journal of Chemical Education, 75(10), 1308-1312.
Directory of Schools Distance Learning Programs. (2006). Retrieved July 2, 2005, from www.directoryofschools.com/distance-learning.htm
Forinash, K., ; Wisman, R., (2001) The viability of distance education science laboratories. T.H.E. Journal, 29(2).
Freeman, H. E., Lipsey, M. W., ; Rossi, P. H. (2004). Evaluation: a systematic approach (7th ed.).Thousand Oaks, California: Sage Publications, Inc. (Original work published 2004).
Gall, M. D., Gall, J. P., ; Borg, W. R. (2003). Educational Research (7th ed.). New York: Author. (Original work published 1963) Directory of Schools Distance Learning [Data file]. Available from http:// www.directoryofschools.com/ distance-learning.htm
Glenn, A.S., (2001) A comparison of distance learning and traditional learning environments. Dissertation Abstracts International, (UMI No. 3007263).
Gorsky, P., Caspi, A., ; Tuvi-Arad, I. (2004). Use of instructional dialogue by university students. Journal of Distance Education, 19(1), 1-19.
Hauck, W. (2006).Online versus traditional face-to-face learning in a large introductory course. Journal of Family and Consumer Sciences, 98(4).
Hjorth-Gustin, P. (2004). The effectiveness of teaching introductory chemistry online. Dissertation Abstracts International, (UMI No. 3124543).
Kahveci, A. (2003, July). Chemistry at a distance: instructional strategies and the internet component of the courses-a chronological review of the literature. Turkish Online.
Kimbrough, J. ; Reeves, J. (2004). Solving the laboratory dilemma of distance learning general chemistry. Journal of Asynchronous Learning Networks, 8, 3.
Kahveci, A. (2003). Chemistry at a distance: instructional strategies and the Internet component of the courses-a chronological review of the literature. Journal of Distance Education, 4(3). Retrieved February 20, 2006, from http://tojde.anadolu.edu.tr/tojde11/articles/kahveci.htm
Kennepohl, D. ; Last, A. M. (2000). Teaching chemistry at Canada’s Open University. Distance Education, 21(1), 183-197.
Kim, H. ; Kusack, M. (2005). Distance education and the new MLS: The employers perspective. Journal of Education Library Information Science, 46(1).
Liu, D. (1996). Teaching chemistry on the internet. Dissertation Abstracts International, (UMI No. 9708072).
Madore, K. A. (1998). Learning at a distance: the experiences and attributional style of secondary students in an audiographics teleconference chemistry course. Unpublished master’s thesis, Memorial University of Newfoundland, Canada.
Maguire, L. (2005). Faculty participation in online distance education: barriers and motivators. Online Journal of Distance Learning Administration, 8(1). Retrieved July 3, 2007, from http://www.westga.edu/~distance/ojdla/spring81/maguire81.htm
Meta-Analysis Software Comparison. (2006). Retrieved July 1, 2007 from http://www.meta-analysis.com/pages/why_use.html
Patterson, M. J. (2000). Developing an internet-based chemistry class. Journal of Chemical Education, 77(5), 554-555.
Rice, L. (2004). Distance education: the introduction to college chemistry course. Dissertation Abstracts International, (UMI No. 3134688).
Spevak, A. (2004). Describing the on-line graduate science student: an examination of learning style, learning strategy, and motivation. Dissertation Abstracts International, (UMI No. 3128583).
Taylor, S. ; Todd, P.A.(1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
Vroeginday, B. (2005). Traditional vs. online education: a comparative analysis of learner outcomes. Dissertation Abstracts International, (UMI No. 3193436).
Willis, B. (2000). Distance education best kept secrets. The Technology Source [Online]. Retrieved September 3, 2007, from http://www.technologysource.org/article/distance_educations_best_kept_secrets/