Student Success in Online K-12 Education

As many states respond to student populations that are growing faster than campus facilities can be built, online learning (also known as, distance education or e-learning) has been described as “the ‘next wave’ in technology-based K-12 education” (Clark, 2000). For a nation whose public and private schools have already experienced 19% enrollment growth from 1998-2001, the additional increase of 5% which is expected through 2001-2013 will continue to further strain the education system in the United States in the years to come (National Center for Education Statistics, NCES, 2003). As a result, virtual schools— public, private, and charter—are emerging in many states as an option that can fill the gap in serving students without the capital expenses required for school facilities.

Such schools are not often viewed as a replacement for traditional schools, but rather as an approach that can expand their curricular offerings and serve student populations not participating in classroom-based education by necessity or choice (Clark, 2001). Traditionally under-served populations, including students who are home-schooled, have health conditions, are at high-risk for dropping out, or have competing personal or professional commitments (i.e., competitive athletes), have been among the early adopters of online learning as an alternative to the traditional classroom K-12 education.

As of 2002, 12 states had active online school programs, another five states were developing online options, 25 states had legislation permitting the creation of online charter schools, and a total of 32 states had e-learning initiatives in some form (Education Week, 2002). And, according to a 2002 survey conducted by Interactive Educational Systems Design, Inc., nearly 41% of public secondary schools offered some online courses (Manzo, 2002). It is estimated that 40,000-50,000 students enrolled in online courses in 2001-2002, with a majority of students taking online courses as part of their regular course load. As a result, many students participate in their online courses at specific times during their day on the traditional campus (Clark, 2001).

While online K-12 education is a relatively new option for students in many states, distance education as a viable—and sometimes preferable—approach to education has gained noticeable acceptance among parents, educators, and the public. For example, Clark (2001) reported on a 2001 Phi Delta Kappa and Gallup Poll of 1,108 adults. In the poll, 30% of respondents approved of allowing students to earn high school credit over the Internet without attending a traditional school, not far behind the 41% who approved of the longestablished home schooling (as cited in Clark, 2001). In addition, many employers are also realizing the qualified and capable job candidates are often-times utilizing “alternative” routes to gain the education they require (Mulrean, 2004).

Accessibility to information is an essential variable in the quality of education for today’s children. For most, the good news is that, as of 2000, 98% of public schools had access to the Internet. In addition, the nationwide ratio was one computer to every five students (NCES, 2002). The Pew Internet and American Life Project survey further found that three in every five children under the age of 18 and nearly eight of every 10 children between the age of 12 and 17 use the Internet (Pew Research Center, 2002). As a result, by using the technology that is widely available to school children across the county, we can now offer children a viable alternative to traditional classroom courses.

Online K-12 schools can be defined as “educational organizations that offer K-12 courses through the Internet or Web-based methods” (Clark, 2001). Many virtual schools exist to expand access to high quality or rigorous curricula, serving rural areas and special learner groups such as gifted or at-risk students. In the survey of online K-12 schools, 91% indicated they offered regular high school courses, 73% offered remedial high school courses, 61% offered advanced placement credit courses, 49% offered dual enrollment, and 22% offered high school diplomas (Clark, 2001), and the diversity of course offerings across content areas (e.g., English, math, social studies) continues to expand as more schools and teachers make resources available online.

Although entirely online schools are becoming more common, currently virtual schools primarily supplement regular instruction or offer alternative diplomas. Courses are typically taken as part of the student’s regular course load and are often completed during school hours at computers provided by the school. For example, online courses allow schools to expand their curricular offerings to include obscure or low-enrollment courses such as Latin or advanced placement courses (Trotter, 2001). Online courses can also provide a method of remediation for students requiring additional assistance.

A survey conducted by Education Market Research (1998) revealed that more than 50% of K-12 classroom teachers use the Internet as a research or reference tool, which is just the beginning for students taking courses through an online K-12 school. Online students use the Internet to communicate with their peers, ask questions of their teachers, build online learning communities, download lessons, share resources, and develop skills for lifelong learning. For students of online K-12 schools, the Internet is used as both instructional and social support tool to create environments where students can learn, interact, and develop the necessary skills for employment and citizenship; sometimes the online classrooms replicate experiences of the traditional campus classroom, and many times they expand beyond the physical boundaries to provide online students with unique learning opportunities.

While the majority of research on student success in online courses (completion rates, grades, etc.) has been conducted at colleges and universities, the relationship of those findings to the success of online K-12 students has yet to be validated. In this section, we will primarily refer to research conducted with university students, and note that any generalizations to younger students would have to be validated through research before any policy implications can be accurately recommended.

That being the case, several personal and psychological characteristics are often linked with the academic success of online learners (i.e., college students). Such attributes include self-regulatory skills (Brooks, 1997; McMahon & Luca, 2001; Yang, 1993), locus of control (Fazey & Fazey, 2001), self-efficacy skills (McMahon & Luca, 2001; Wang & Newlin, 2002), and motivation (Illinois Virtual High School, 2003;,Wang & Newlin, 2002) are regularly considered important characteristics of successful online students. In addition, prior distance learning experience can be a useful predictor of success (Wang & Newlin, 2002).

McMahon and Luca (2001) state that a “student’s ability to use self-regulatory learning skills is becoming increasingly important with the advent of the World Wide Web-based learning” (p. 427). Such learning skills include meta-cognition, self-concept, self-monitoring, strategy formation, and decision-making strategies. Brooks (1997, cited by McMahon & Luca, 2001) further supported this recommendation when they suggested that students “who are poor at self-regulation easily can be slaughtered in WWW-based courses” (p. 135). Psychological predictors of success include whether the learner has an internal or external locus of control, self-efficacy (in two areas), and student motivations. Students with an internal locus of control (e.g., “The success I have is largely a matter of my own doing”) are more likely to succeed (Fazey & Fazey, 2001) in online courses (Wang & Newlin, 2002). Self-efficacy is important in both understanding the course content and dealing with the technology associated with participating in and completing the online course (Wang & Newlin, 2002). Obsorn (2001) found that “students who have strong confidence in their computer skills and less computer anxiety were more likely to remain in a distance learning class than students with lower levels of computer confidence,” supporting the results of Wang and Newlin’s research revealing the self-efficacy is highly predictive of grades received.

Student motivation also seems to play an important role in their success in online courses. In surveying administrators, counselors, students, and instructors, the Illinois Virtual School (IVHS) identifies student motivation as the most crucial success factor (IVHS, 2003). Existing research (e.g., Kurtz, Sagee, & Getz-Lengerman, 2003; Thomerson & Smith, 1996) indicates students who selfselect enrollment are more likely to complete than those who are forced into online courses.

There are also indications that students whose motivation to enroll for reasons other than just course availability have a higher rate of completion (Wang & Newlin, 2002).

The role of self-regulation, self-efficacy, motivation, and other personal and psychological characteristics in student performance may, however, be mediated by many variables related to the design of the online learning experience. Currently, there is not adequate research on the importance of self-regulation in highly interactive online classrooms that are facilitated by Internet technologies like instant messenger, synchronous chat, and desktop video conferencing. Future research into the evolving role of this and other personal and psychological characteristics within highly interactive online courses should provide applicable information for online teachers and course developers.

Yet, regardless of the interactivity of a distance education course, prior distance learning experience is another factor that seems to impact on student success. Students who complete multiple distance education courses not only take a greater number of college courses, but also earn higher grade point averages than those who drop out (Osborn, 2001). As a possible implication, building online study skills among younger students in K-12 education (e.g., online communication skills, online reading skills, computer-based note taking) may lead to positive results as students expand the use of online resources as part of their K-12 education.

Prior to completely online virtual schools, many K-12 students used technology in the classroom (or computer lab) in the forms of email, word processing, creating spreadsheets and presentations, and conducting research via the Internet. Now, with the advent of completely online schools, technology can be used to transition from isolated skill-building to a true learning tool, such as paper and pencil. Consequently, online schools provide an optional resource for building learning communities that can transcend to critical thinking. Paloff and Pratt (1999) state that “without the support and participation of a learning community, there is no online course” (p. 29). Two factors contributing to community development within online courses are participation and interaction (Lock, 2002). The requirement for frequent and open communication between students and instructor, among students, and between groups of students, is identified as a key component to community development in the online course (Murphy, Mahoney, & Harvell, 2000).

Factors influencing community development include the discipline, structure, and education level of the course, as well as the instructor (Paloff & Pratt, 1999) and the students (Hiltz, 1997). Wang and Newlin (2002) found that students who participated in online study groups had higher final grades than those who studied alone. As a result, building a learning community in an online K-12 course is considered important for student success, yet can be challenging, to say the least. Student characteristics often times influence both participation level and overall community development. Brook and Oliver (2003) identify the following characteristics as influencing factors: “level of education and online experience (citing Hiltz, 1997), perceptions of self as either connected or separate from others (citing Gilligan, 1982), and approaches to communication based on a need for connection or status (citing Gougeon, 2002).”

For example, the Christa McAuliffe Academy in Washington State offers K-12 Internetbased courses and, as part of courses, students can participate in synchronous virtual meetings; a unique aspect of the program that is not available to classroom-only students. “We found a high correlation”, says Principal Blomgren, “between participating in our Virtual Classrooms and succeeding in our how program” (quoted in Clark, 2001).

While there are still many variables related to building online learning communities that must be researched (e.g., online group dynamics, facilitation methods, student characteristics), the importance of developing interactive and engaging online courses continues to be a focus of researchers and practitioners. Using today’s Internet technologies, online courses can however meet the requirement of students for both instructional and social support in the online classroom.

A necessary first step for student success in Web-based education is to assess whether students possess the skills necessary to succeed in this environment. This can be accomplished through the use of diagnostic tools that measure how students use learning strategies in academic environments. Strategies to assess student readiness for success in online course include questionnaires (McMahon & Luca, 2001), lists of successful student characteristics (Wang & Newlin, 2002), and online demonstration courses (Clark, 2001). For example, the Learning and Study Strategies Inventory developed by Weinstein, Palmer, and Schulte (1987) gathers information about learning, study habits, and student attitudes. Similarly, the Online Student Readiness Self-assessment (Watkins & Triner, 2004) offers students a self-measurement tool for determining if they have adequate technical skills, online social skills, and study skills for success in online courses. Such instruments can be used as a pretest prior to the start of the course, followed by customized feedback to assist students in increasing their awareness and skills in areas of deficiency (McMahon & Luca, 2001).

To enhance retention and completion, it has been recommended that students should go through prescreening that encompasses multiple methods. Clark (2001) cites that many schools try to screen out students for whom online learning may not be appropriate. Some schools even provide a grace period after the course begins in which they can withdraw with no penalty (Florida Virtual School Evaluation Report, 2002).

For example, the Florida Virtual School (FLVS), Kentucky Virtual High School, and Illinois Virtual High School offer readiness self-assessment questionnaires and an online demonstration course prior to enrollment. At FLVS, the grace period is 28 days from the start of the course. None of the virtual schools contacted (FLVS, IVHS, and Holliston Public School District) required technology and study skills training prior to enrollment in online courses (R. DuRocher, personal communication, March 6, 2004; M. Wicks, personal communication, March 17, 2004; K. Dooley, personal communication, March 15, 2004).

It is recommended that virtual schools provide additional orientation activities for new online learners (Clark, 2001). One method to enhance learner readiness for participating in the online learning environment is through adequate preparation prior to the start of the course. “Rookie Camp” (Niemczyk, Dwyer, & Saveyne, 2000), is taken as the first module in an online course. Students prepare to succeed by gaining competencies in using the navigational and discussion tools that are part of the course. Rookie Camp includes a reminder card for note taking and a mnemonic device representing the names of the Web-environment icons. In an evaluation of sixth through ninth grade students representing both ends of the academic spectrum of low and high achievers, 100% were able to provide correct names of icons one week after participating in Rookie Camp. However, only one of three of the lowachieving students were able to correctly provide descriptions for these icons. This raises interesting questions about the applicability of Web-based learning for low-achieving students. Given the small sample, further research is needed to determine the issues associated with low achieving students participating in online instruction.

Wang and Newlin (2002) recommend online instructors adopt several early warning indicators of student performance. Their research findings indicate self-efficacy and motivation are situational in nature and therefore must be pursued by the instructor in addition to activities to determine suitability for online learning prior to enrollment.

The students attending online K-12 schools are representative of the community served by school, although technology access and skills often times skew the representation. In 2004-05, the majority (69%) of the student population was White; minority populations enrolled included Hispanic (13%), African-American (8%), Asian (4%), multi-ethic (4%) and other (2%) (Florida Virtual School, 2004). A Florida Virtual School Parent Survey in 2000-01 (Optimal Performance, Inc., 2001) revealed 62% of students participating in online courses at FLVS were currently enrolled in public schools, 28% were home schooled; and 6% attended private schools; and slightly more students are female, 53% compared to 47% male.

Many indicators can be used to measure success of online K-12 education programs; fundamental indicators traditionally include academic performance (successful completion), retention (enrolling in future courses), academic achievement (performance and grade distribution), and stakeholder satisfaction (parent, student, teacher, etc.). Currently researchers utilize a variety of these to determine the success of online schools, and no single indicator has been developed to evaluate success.

The Illinois Virtual High School, for example, experienced significant improvement in its student completion rates between spring 2001 and spring 2002. The completion rate for the spring 2001 semester was 53%. For the next academic year, fall 2001-spring 2002, the completion rate was 80%, with an enrollment of 425 students. The only identified attribute to this improvement is programmatic experience in delivering online instruction (IVHS, 2003).

Programmatic experience is the operational knowledge gained by the institution as online courses are offered over a period of time.

Likewise, the Florida Virtual High School had difficulty living up to its motto, “Any time, any place, any path, any pace,” and had to replace their open pacing model. Students pursuing the any pace model suffered poor completion rates. Now, the school offers three pacing options: accelerated, standard, and extended (Clark, 2001).

The FVHS completion rate for the 2002-20003 academic year was 94%, 91% in 2001-2002, and 81% in 2000-2001. High completion rates can possibly be explained through the ardent efforts of advisors to make sure the students are right for this mode of learning. Students who are not independent are encouraged to drop the course during the grace period. There is little data available on students who drop out. Students may decide online learning is not for them in the first 2 weeks. No information is tracked on these students. Future research should explore characteristics in this population group for trend identification. Interestingly, K. Dooley (personal communication, March 15, 2004) notes there are no students in the lowest group of class rank participating in online learning at Holliston Public School District.

Success can also be measured in terms of academic achievement, including grades earned and performance on advanced placement examinations. A majority of online students earned grades of B or better (K. Dooley, personal communication, March 15, 2004). For the 2000-2001 academic year, FLVS advanced placement qualifying scores exceeded the national average by nearly 9% (70% vs. 61%). In addition, the percentage of FLVS students scoring 4s and 5s was 50%, compared to the national average of 33%. (Optimal Performance, Inc., 2003). K. Dooley (personal communication, March 15, 2004) and M. Wicks (personal communication, March 16, 2004) both note that the success of online students, both in grades earned and test performance, could be attributed to the quality of student admitted to virtual schools and to the pre-screening done to ensure match of student characteristics and online learning.

Another aspect in the success of virtual schools is the satisfaction level by stakeholder groups. Stakeholders include students, parents, school districts, teachers, and ultimately employers. A majority of data available in this area comes from the Florida Virtual School, a recognized leader in K-12 online education. Other than the FLVS Evaluation Reports (Optimal Performance, Inc., 2001, 2003), there is little data published on stakeholder satisfaction; even the FLVS report does not address any satisfaction by employers. This could be due to the relatively new nature of online learning. Future research should examine the level of satisfaction by employers in comparison to students from classroom-based programs.

Online learning is relatively new in delivering instruction to K-12 students. It clearly presents opportunities to expand curricular offerings and regain students formerly not participating in public education. However, further research is required in many areas to overcome challenges such as student preparation, the intellectual divide, student success, and satisfaction of all stakeholder groups, building community, and predictors of success. Much of the existing research focuses on college students who are older and more mature. Additional research to determine the applicability of these factors to K-12 online learners could be beneficial to educators (Wang & Newlin, 2002). This is considered crucial in applying what has been learned through online learning research in higher education to the K-12 classroom. Studies are also necessary within K-12 to confirm applicability of higher education findings. Future research should also examine if students participating in online courses are better prepared to succeed in college and the workplace.

Currently, it is challenging (at best) to determine how successful distance education has been for K-12 students. Beyond offering opportunities to learn, we are just now beginning to find data on what it takes for a student to be successful in a distance learning classroom and how we can both assess and prepare students more effectively to manage this transition. Online K-12 education is here to stay, and growing rapidly. As a result, it is critical for researchers to be leaders in the field and offer guidance to the private, public, and charter schools that are making the Internet an active school yard.