The Effects of Distance Education on K-12 Student Outcomes: A ...

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Figure 2. Confidence intervals for individual effect sizes <strong>of</strong> 116 outcomes 1.5 1.0 0.5 0.0 -0.5 -1.0 -1.5 -2.0 Confidence Intervals for Individual Effect Sizes Of the 45 factors coded in the study, the following 30 were examined to determine sources <strong>of</strong> significant variation in effect sizes. Ten <strong>of</strong> the remaining variables were used for identifying the studies or computing effect size, and the other five could not be compared because the studies did not include the data for coding the variables, or the variable was not a relevant factor in the studies. <strong>The</strong> variables that went uncoded due to the absence <strong>of</strong> data were the frequency <strong>of</strong> student participation in distance learning, the level <strong>of</strong> preparation <strong>of</strong> the teachers in distance education, and the amount <strong>of</strong> experience <strong>of</strong> the teachers in distance education. <strong>The</strong> variables that were not relevant factors for the studies were control for the effects <strong>of</strong> a second testing, and control for the effects <strong>of</strong> a pretest. Analysis <strong>of</strong> variance was not meaningful for some <strong>of</strong> the variables because <strong>of</strong> missing data in the studies, resulting in a high number <strong>of</strong> cases in which a value <strong>of</strong> “unspecified” was coded for the variable. Publication and Methodological Variables Twenty variables were coded to discover whether publication or methodological variables accounted for variation in effect sizes. <strong>The</strong> publication features included the year <strong>of</strong> publication, the type <strong>of</strong> publication, and the region <strong>of</strong> publication. <strong>The</strong> methodological variables related to the testing sequence in the study, the type <strong>of</strong> achievement measure used in achievement studies, pretest equivalency measures, study design, statistical power, and control for 12 potential sources 14 <strong>of</strong> 32
<strong>of</strong> invalidity. None <strong>of</strong> the variable comparisons resulted in effect sizes significantly different from zero. <strong>Distance</strong> <strong>Education</strong> Variables Eleven variables were used to identify the features <strong>of</strong> the distance education experience that may play a role in student performance. <strong>The</strong>y were duration <strong>of</strong> the program, frequency <strong>of</strong> use <strong>of</strong> distance learning, instructional role <strong>of</strong> the program, number <strong>of</strong> distance learning sessions, duration <strong>of</strong> distance learning sessions, pacing <strong>of</strong> the instruction, role <strong>of</strong> the instructor, timing <strong>of</strong> the interactions, type <strong>of</strong> interactions, amount <strong>of</strong> teacher preparation for distance instruction, and amount <strong>of</strong> teacher experience in distance instruction. Because <strong>of</strong> the individualized nature <strong>of</strong> distance education, only two <strong>of</strong> the studies indicated specific numbers and durations <strong>of</strong> distance learning sessions, and they were studies <strong>of</strong> limited partial-course experiences. Half <strong>of</strong> the studies did not indicate whether students or instructors set the pace within the distance learning timeframe, while three <strong>of</strong> the programs were completely self-paced, and four were designed for students to set their pace within parameters set by the instructor. In terms <strong>of</strong> the role <strong>of</strong> the instructor in teaching, one program was fully moderated, five were non-moderated, four used a combination <strong>of</strong> moderated and non-moderated activities, and four did not indicate the instructors’ role. Ten programs used a combination <strong>of</strong> interactions among students, content, instructors, and others; one limited interactions to student-content; and three did not specify interaction types. No studies described the levels <strong>of</strong> instructor preparation or experience required <strong>of</strong> or possessed by the instructors. All levels <strong>of</strong> each distance education variable had effect sizes not significantly different from zero. Instructional and Program Variables <strong>The</strong> five variables that indicated the extent to which instructional and program factors played a role in student outcomes were grade level, school type, content area, the qualifications <strong>of</strong> the teacher in the teaching field, and the setting <strong>of</strong> the students. Twelve <strong>of</strong> the studies indicated that the instructors were certified teachers, and the other two studies did not describe the credentials <strong>of</strong> the instructors. In five <strong>of</strong> the programs, students participated from home or a non-school location, four programs are designed such that students completed some work from home and some in a school setting, in three programs, students did their distance learning work while at a school, and two programs did not specify the setting <strong>of</strong> the students. All instructional and program factors had effect sizes that were effectively zero. Discussion <strong>The</strong> literature reviewed in this meta-analysis includes results from 116 comparisons <strong>of</strong> grades 3- 12 web-based distance education programs with classroom-based teaching, including data for 7561 students. <strong>The</strong> questions <strong>of</strong> the effectiveness <strong>of</strong> distance education for K-12 student performance, and <strong>of</strong> the factors influencing its effectiveness were addressed using fixed-effects effect size estimation. <strong>The</strong> findings confirm those <strong>of</strong> other recent meta-analyses <strong>of</strong> distance education programs, and provide a needed update to the meta-analysis focused on K-12 students 15 <strong>of</strong> 32
Page 1 and 2: The Effect
Page 3 and 4: The Effect
Page 5 and 6: are inherently interesting and mean
Page 7 and 8: 4. To what extent are results relat
Page 9 and 10: Abstracts in American Educa
Page 11 and 12: encompassing zero, is an indication
Page 13: programs in which students particip
Page 17 and 18: professional devel
Page 19 and 20: a rather short-sighted view <strong
Page 21 and 22: References References marked with a
Page 23 and 24: Fording, L. (2004). Educati
Page 25 and 26: * Stevens, K. (1999). Two Canadian
Page 27 and 28: 9. Content area (“content”). Un
Page 29 and 30: Other=5. 4. Setting of</str
Page 31 and 32: 6. Statistical Regression (“regre

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