Candace Byrne

         We who teach in collaborative environments are warmed and invigorated by comments like these, written by students in end-of-term self-evaluations of their participation in collaborative groups. Such responses in student self-evaluations, and the palpably energized learning environments we've witnessed all term, convince us-and our students-of the value of collaborative learning. Unfortunately, they aren't enough to convince the skeptics, whether the faculty member who wonders about "coverage" in collaborative settings or the dean who must make funding decisions in times of shrinking resources. These colleagues need another kind of evidence, and we can provide it, as well, by designing simple studies using easily available data.

         Many institutions, even if they haven't launched full-scale research to assess the effectiveness of collaborative learning or learning communities, have devised studies that use such data to compare student retention and success in collaborative settings with that of students in traditional settings. Likewise, many instructors teaching in collaborative learning classrooms have themselves begun to assess the effectiveness of their work, either because their institutions lack an institutional research office or, simply, because the instructors themselves want quantifiable confirmation of their sense that students who work collaboratively enhance their learning.

         Institutions which track student success in learning community programs use the easily accessible data tracking student retention, where retention is defined as the number of students registered on the tenth day who also complete the course. (See Gail Wilkie's article in this Handbook for a more detailed institutional research approach.) Many institutions in Washington state keep these records, and several also provide average institutional retention rates, which can be used for comparison. A few examples follow, all of which show higher retention in the learning community than in the institution as a whole.

       Some instructors use more elaborate data to conduct similar quantifiable studies. Two biology instructors at Yakima Valley Community College, Judy Moore and Eric Mould, used retention rates and grade distributions to compare student success in their sections of Biology 101 before and after implementing a collaborative learning approach to the course. (See Moore and Mould's article elsewhere in this Handbook). They compared retention and grade distribution rates from their last twelve sections taught in the lecture mode to those in the first twelve sections taught using their new design with collaborative learning strategies. Before they implemented the collaborative learning approach, their retention rates (80%) were already markedly higher than the institutional average (63%). After implementing the collaborative learning approach, their retention rates climbed even higher. (See Figure 2.)

         These numbers mean that only two to three students in a typical section failed to complete Bio 101. Judy and Eric also note that, with the new collaborative approach, students rarely drop after the third week, while under the lecture method, students dropped throughout the quarter. They attribute their increased retention to the supportive community that students develop in the collaborative learning classroom.

       Although the new, collaborative approach demands more from the students, they earn higher grades than those earned by students in the Biology 101 lecture classes. (See Moore and Mould's article for a description of the different kinds of test questions they ask in the class using the collaborative approach.) The data show an increase in numbers of students earning A's and B's and a decrease in numbers of students earning D's and F's. Judy and Eric believe this shift illustrates the synergistic effects of students learning together throughout a whole term. As instructors have long testified, we truly learn a topic when we have to teach it. Students in these sections, because they are daily responsible for teaching each other and puzzling out problems together, learn the material, and their grades reflect their learning.

         Many instructors similarly compile data to confirm their intuition and students' reports on end-of-term self-evaluations. Two instructors at Spokane Falls Community College, Diane DeFelice and Jan Swinton, also worked with Biology 101. They linked Bio 101 with two versions of a study skills class, the first one a developmental level and the second one a transfer level course. The first enrolled 25 students who had scored below average on entrance reading and writing tests; these students took Bio 101 and the developmental level study skills class concurrently. The students met with both instructors for a two hour/day block and an additional lab section each week. The graph in figure 3 compares grade distribution in this paired biology class with grade distribution in a free-standing biology class taught by Diane the same quarter. In this case, the tests in the two different sections, one stand-alone and the other linked, were essentially the same types of tests on essentially the same material.

       Two features seem most striking. First, fewer students earned D's and F's in the paired class (ten in the free-standing class, six in the paired class). Although the disparity in grades between the two classes lessens when D's, F's, and W's are compared (twelve in the free-standing class, eleven in the paired class), it is important to remember that all students in the paired class scored below average on reading/writing placement tests.

         The second area of contrast in overall student performance between the two classes is the difference in the number of C grades. "Typically," Diane comments about Bio 101, "a significant number of students receive A's and B's, a significant earn D's and F's, and only a few are in the middle [C's]. This creates an inverted curve, which isn't unusual in beginning science classes." Even though the paired Bio 101 class enrolled all developmental level students, the grade distribution resulted in a much more bell-shaped distribution.

       Figure 4 shows the grade distribution among students enrolled in a Bio 101 class paired with a transfer level study skills class in Fall, 1993, compared with that among students enrolled in Diane's stand-alone Bio 101 in Fall, 1992.

The class sizes differ (36 students represented in the paired class, 46 in the stand-alone class), but the paired class shows a considerably higher success rate (75%) than the stand-alone class (63%), if success is measured by numbers of students who earn A's, B's and C's.

         Both pairs of instructors - Judy and Eric, Diane and Jan - used easily accessible data on student retention and grades in the courses and achieved better than students in comparable, more conventional classes. These instructors' data provide useful evidence of some quantifiable successes with collaborative learning/teaching - data which, like the institutional results which show greater retention in learning community courses than in the average course may serve them well. We who use these methods can begin collecting such data. They will provide doubters with evidence of some of what happens in our collaborative settings. And they just might prove as rewarding and confirming as the snippets from student self-evaluations we have long collected in our desk drawers.

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