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Distance Learning Articles
1. Adding Up the Distance 2
2. Bridging the Gap: A Community College and Area High Schools Collaborate To Improve
Student Success in College 6
3. Is the Sky Still Falling? 23
4. Student Preferences, Satisfaction, and Perceived Learning in an Online Mathematics
Class 29
5. New Directions for Dual Enrollment: Creating Stronger Pathways from High School
through College 43
League for Innovation in the Community College
http://www.league.org/league/about/press/plato_distance_learning.htm[12/6/2011 11:19:18 AM]
PLATO Learning ReleasesResults of Major DistanceLearning Study
'Adding Up the Distance' study completed in conjunction with the Leaguefor Innovation in the Community College
BLOOMINGTON, MINN. (June 26, 2000) - It is no secret that many students whoenroll in college are unprepared for the academic rigors of college work. Theoverwhelming numbers indicate that nearly one-half, or 44 percent, of studentsentering 2-year colleges each year require some form of remediation. The numberof students underprepared for college level work is amplified by the variety ofdevelopmental learners' needs. The needs and academic plans are clearly not thesame for a 40-year-old woman returning to college for job development skillsafter being out of school for 22 years and an 18-year old high school student whogoofed off in math class. Nor are they the same for a student who graduatedfrom an inner-city high school that did not offer advanced algebra classes and ahighly skilled math student whose native language is not English. Internet-basedlearning is increasingly utilized to help these students quickly get up to speed intheir courses.
In the spring of 1999, the League for Innovation in the Community College andPLATO Learning initiated a joint research project exploring the questions andchallenges of implementing successful distance learning developmental mathprograms for community colleges across the country. Eight colleges participated inthe study and the findings will be released at the Conference on InformationTechnology, Nov. 15-18 in Anaheim, Calif., as "Adding up the Distance: CriticalSuccess Factors for Internet-based Learning in Developmental Mathematics."
Each year, more than $1 billion is spent to provide remedial services to incomingcommunity college students," said Dr. Rob Foshay, Vice President of InstructionalDesign and Cognitive Learning at PLATO Learning. "This research project focusedon identifying how the Internet, distance learning techniques, and PLATO Learningcan work together to more effectively serve the developmental needs of students.This is a significant step in PLATO's ongoing commitment to expand our Internetofferings. Our project partners are national leaders in postsecondary educationand we are excited to have had the opportunity to work with them in this effort."
According to Edward Leach, Vice President-Technology Programs at the League forInnovation: "The Internet has opened powerful new doors to education. TheLeague is pleased to have participated in this project to further define the bestpractices for using online technologies to enhance student success indevelopmental mathematics."
The project explored "critical success factors" for computer-based distancelearning in developmental math programs during a summer trial implementationsession and a full fall semester term. Mathematics was chosen because it is the
League for Innovation in the Community College
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subject area of perhaps widest need in developmental studies, and because itscontent and measures are relatively well defined. College participants, Leagueresearch team members, and PLATO service teams worked together in fourprincipal areas of investigation:
Development of effective, individualized, open entry/open exit programs fordevelopmental students via distance education.Cultivation of learners' motivation through the use of technology indevelopmental studies programs using distance education.Exploration of successful developmental student profiles using distancelearning technology.Effective combinations of campus-based support service and distancelearning delivery systems as models of success for developmental learners.
The project began by exploring college administration, instructors, and students asindependent variables of distance learning developmental math programs andcontinued with an investigation of best distance learning practices. Extensive dataanalysis allowed PLATO and League researchers to draw some conclusions aboutthe interdependent relationship of college resources, instructors, and learners insuccessful distance learning models.
The colleges that were most successful with students created a systemic andconnected balance in their distance learning developmental math programs.According to the preliminary project results, the 10 factors that appeared to bemost critical to success of these programs are summarized below and will beexplained in greater detail within the final "Adding Up the Distance" report.
Development of individualized, open entry/open exit, effective programsfor developmental students via distance education.
Beyond the traditional functions of student services and development of courseobjectives, distance learning services and curriculum should be enhanced toinclude a more comprehensive plan with the following variables.
1. Easy Access to Internet and Easy Navigational Courseware - Although themajority of students who enrolled in distance learning courses expressed highlevels of comfort and expertise with computer-based applications, courseware thatmakes logon/logout functions and transition from lesson to lesson as smooth aspossible was cited as a recognized benefit to successful students.
2. Technical Support - Over and over again technical support (via collegehelpdesk or program contact) reigned as the most important factor cited by bothstudents and faculty to program success.
3. Alignment of Online Courseware and Course Objectives - Those programsthat correlated course objectives with Internet courseware lessons in a meaningfulway (whether as supplemental or primary content) and connected assignmentsand class activities had more successful outcomes than those programs who usedthe Internet courseware as a drill-and-practice exercise.
4. Individualized Instructional Format - Faculty who used the computer-adaptive components of the Internet courseware management system and offeredindividualized and targeted assignments for students were recognized morefavorably by students. Students and faculty noted the self-paced, individualized,any-time/any-place functions of distance learning as the best features of theproject.
Development of successful student profiles using distance learning
League for Innovation in the Community College
http://www.league.org/league/about/press/plato_distance_learning.htm[12/6/2011 11:19:18 AM]
technology.
5. Student Recruitment and Counseling - Proactive selection, preparation, andcounseling with students entering distance learning programs were noted as keyvariables for success and course completion. Students who demonstrated a senseof motivation, time management, and program/academic goal were moresuccessful in the project.
6. Orientation - Students who attended mandatory group orientations had fewtechnical problems, experienced greater ease of navigation, and had successfulprogram outcomes.
Cultivation of learners' motivation through the use of technology indevelopmental studies programs using distance education.
7. Student Connections - Interactive and frequent contact was an importantcondition for success. Although many students appreciated the self-paced andindividualized format of the Internet courseware, they were quick to note thatwhen questions or issues were resolved via a Web page contact, email, or phonecall, there were higher levels of satisfaction with the course and comfort levelwith technology. The successful programs in the study had structured assignmentschedules with student contact requirements as part of course activities.
Combination of campus-based support service and distance learningdelivery systems as models of success for developmental learners.
8. Faculty Development - Faculty participants had varying levels of experiencewith technology and computer-based applications. Those colleges who offeredmore than five professional development opportunities correlated with faculty whowere active in attending workshops and conferences. The faculty from thesecolleges created successful programs in this project.
9. High Standards of Quality and Content Development - As might beexpected, faculty who had experience with distance learning had successfulprogram outcomes, however in a few instances, faculty who were using distancelearning as a developmental math option for the first time were also verysuccessful. From the research data gathered, it is concluded that the "first-timesuccessful faculty" showed great interest in computer-based applications and self-initiated the learning curve of teaching with technology. Rather than tag on a fewlessons with existing course assignments, they closely reviewed Internetcourseware content and were actively involved in new curriculum developmentand content upgrade for their courses. They were also very active in seekingtechnical support and assistance from the PLATO helpdesk and their assignedPLATO educational consultant.
10. College Leadership & Program Support - Participating colleges thatdesignated priority, support, and commitment of resources for technicalinvestments to this project clearly saw successful responses from faculty andstudents. Although transparent in some instances, administrative support wasrecognized as clearing the way for successful implementation, programdevelopment, and student access leading to high quality services and learningopportunities for students.
"Behind these critical success factors is the hard work, dedication to innovation,and commitment to learning shared by administrators, faculty, and studentparticipants," said Dr. Foshay. "Although the project traced the ideas, progress,and outcomes of students over two short semesters, the need to expand and leadfurther research efforts in distance learning for developmental education should bepart of the investment in our college, community, and country's future. Ifcommunity colleges are to journey from the place-bound world of classrooms and
League for Innovation in the Community College
http://www.league.org/league/about/press/plato_distance_learning.htm[12/6/2011 11:19:18 AM]
computer-labs within campus walls to the anytime/anyplace expanse of distancelearning, it is imperative that studies like these chart our course and guide ouractions towards a destination of knowing," Dr. Foshay concluded.
Participating CollegesThe participating colleges included a considerable diversity of program structureand size. While all participating colleges had well-established campus-baseddevelopmental math programs, they had varying degrees of history andexperience with technology in their developmental studies programs. Theparticipants included:
Central Florida Community College, Ocala, FloridaDelta College, University Center, MichiganKapiolani Community College, Honolulu, HawaiiKirkwood Community College, Cedar Rapids, IowaMoraine Valley Community College, Palos Hills, IllinoisMiami-Dade Community College, Miami, FloridaSanta Fe College, Gainesville, FloridaSinclair Community College, Dayton, Ohio
League for Innovation in the Community CollegeThe League for Innovation in the Community College, as a nonprofit educationalconsortium of resourceful community colleges, stimulates experimentation andinnovation in all areas of community college development and serves as acatalyst, project incubator, and experimental laboratory for all communitycolleges. The League for Innovation in the Community College headquarters arelocated at 4505 East Chandler Boulevard, Suite 250, Phoenix, Arizona 85048-7690. The telephone is (480) 705-8200. For more information, visitwww.league.org.
PLATO LearningWith revenues of over $44 million, PLATO Learning, Inc. is a publicly heldcompany traded as TUTR on the NASDAQ-NMS. Offering more than 2,000 hoursand 10,000 learning objectives of comprehensive academic and applied skillscourseware designed for adolescents and adults, PLATO Learning Systems aremarketed to middle and high schools, colleges, job training programs, correctionalinstitutions, military education programs, corporations, and consumers. PLATO isdelivered via networks, CD-ROM, private intranets, and the Internet.
An international training and education company, PLATO Learning's headquartersare located at 10801 Nesbitt Avenue South, Bloomington, Minnesota, 55437.Phone (952) 832-1000 or (800) 869-2000. PLATO Learning has domestic officeslocated throughout the United States, and international offices in the UnitedKingdom and throughout Canada. PLATO Learning has international distributorslocated in Puerto Rico, Singapore, South Africa, and the United Arab Emirates.The company's Web site address on the Internet's World Wide Web iswww.plato.com.
HOME | SEARCH | SITE MAP | iStream | LEAGUE STORE | WEBMASTER League for Innovation in the Community College
4505 East Chandler Boulevard, Suite 250 · Phoenix, Arizona 85048 · Voice: (480) 705-8200 · Fax: (480) 705-8201Copyright © 1995 - 2011 League for Innovation in the Community College. All rights reserved.
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Community College Journal ofResearch and PracticePublication details, including instructions forauthors and subscription information:http://www.tandfonline.com/loi/ucjc20
BRIDGING THE GAP: ACOMMUNITY COLLEGEAND AREA HIGH SCHOOLSCOLLABORATE TO IMPROVESTUDENT SUCCESS IN COLLEGELaura Berry aa North Arkansas College, Harrison, Arkansas, USA
Available online: 15 Dec 2010
To cite this article: Laura Berry (2003): BRIDGING THE GAP: A COMMUNITY COLLEGEAND AREA HIGH SCHOOLS COLLABORATE TO IMPROVE STUDENT SUCCESS IN COLLEGE,Community College Journal of Research and Practice, 27:5, 393-407
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BRIDGING THE GAP: A COMMUNITY COLLEGE ANDAREA HIGH SCHOOLS COLLABORATE TO IMPROVESTUDENT SUCCESS IN COLLEGE
Laura BerryNorth Arkansas College, Harrison, Arkansas, USA
The Institutional Research Officer and Vice President of Student Services fromNorth Arkansas College, and the Mathematics Facilitator at the local educationalcooperative have initiated a tracking study to determine (1) if area students whotake college preparatory math courses in high school place into, and succeed in,subsequent college-level math courses at North Arkansas College and (2) if areastudents who come to college for a degree have taken sufficient college preparatorycoursework in high school. The study disclosed that (1) students who take a highschool course more rigorous than Algebra 2 place into, and succeed in, CollegeAlgebra at a high rate, and (2) most students have not taken sufficient collegepreparatory coursework in math. The second, and more important part of theproject, has been to bring college and high school personnel together to work onsolutions.
College may not be for everyone, but it should be attainable for stu-dents who complete high school and have a view toward progressing tothe next educational level. Instead, students with the ink barely dryon their high school diplomas enroll in college but find themselvesback in high school level (or lower) remediation courses. What hasgone wrong?
National and regional studies help explain what is wrong byreminding us of what we knew all along—that rigorous high schoolcurricula prepare students for college. Or as Jago (2000) states, ‘‘it’sthe curriculum, stupid.’’ Studies consistently show that the quality ofhigh school education overrides other factors in college success.Answers in the Toolbox (Adelman, 1999), a 15-year longitudinal studyof the factors which affect college success, found that:
Address correspondence to Laura Berry, Director of Institutional Research & As-sessment, North Arkansas College, 1515 Pioneer Drive, Harrison, AR 72601.E-mail: [email protected]
Community College Journal of Research and Practice, 27: 393–407, 2003
Copyright # 2003 Taylor & Francis
1066-8926/03 $12.00 +.00
DOI: 10.1080/10668920390129004
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� The association between degree completion and academic resources(high school curricula, test scores, and class rank) is much greaterthan the association between degree completion and socioeconomicstatus.
� High school curriculum is consistently a better predictor of bache-lor’s degree attainment than test scores or class rank=GPA.
� Of all pre-college curricula, the highest level of mathematics onecompletes in secondary school has the strongest association withbachelor’s degree completion. For those who enter postsecondaryeducation, having completed a course beyond the level of Algebra 2more than doubles the odds of completing a bachelor’s degree.
The authors of The Condition of Education 2000 (U.S. Departmentof Education, 2000) have concluded that students with certain riskfactors, such as low income or parents without postsecondary educa-tion, were less likely to persist in four-year college programs. Butthese risk factors only affected persistence for students who had notcompleted rigorous high school curricula. In an earlier report, Adel-man (1996) concluded that ‘‘the extent of a student’s need for reme-diation is inversely related to his or her eventual completion of adegree.’’ Again, it’s the curriculum.
WHY DO WE CARE?
Educational level is positively correlated with higher incomes(‘‘Family Income,’’ 2000), and educators in Arkansas are well aware ofthe economic consequences of low college attendance and lack ofcompletion. As a low-income, low-education state with remediationrates hovering around 50%, Arkansas is tied for last among the statesin bachelor’s degree completion (Chronicle of Higher Education, 2001,August) and has lost ground relative to the rest of the country duringthe 1990s (Johnston & Hardin, 2001).
Measuring Up 2000 (2000) has awarded Arkansas a grade of D for itspreparation for higher education, a D7 for participation in highereducation, and a Dþ for higher education completion. The ArkansasDepartment of Higher Education estimates that if Arkansans had theaverage education and associated income of the U.S., state revenuesand the budget could be from $2 to $7 billion more each year (Johnston& Hardin, 2001). Mortenson, a policy analyst with PostsecondaryEducation Opportunity, suggests that ‘‘the only thing more expensivethan going to college is not going to college’’ (Mortenson, 2002).
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The statement applies to individuals, but states also suffer the con-sequences of a poorly educated populace.
College-bound students are not the only ones who need remedia-tion. The National Commission on the High School Senior Year (2001)concluded that ‘‘freshly minted high school graduates are equallyunprepared for the literacy, computation, and problem-solvingdemands of the modern high performance workplace.’’ The Commis-sion recommends that high schools stop functioning as ‘‘sortingmachines’’ for college- and workforce-bound students.
REMEDIATION IN ARKANSAS
Almost 60% of first-time freshmen who entered Arkansas publiceducation in Fall 2001 were placed into remediation in at least onearea, and 34% needed remediation in all three areas: math, English,and reading (Harrell, 2001, April). Two-year colleges bear a largerportion of the remedial load than do four-year institutions—in Fall2001 69% of the cohort who entered two-year schools placed into mathremediation, 50% placed into English remediation, and 39% intoreading remediation (Harrell, 2001).
HISTORY OF THE STUDY
North Arkansas College (Northark) is a comprehensive communitycollege serving a five-county area in northwest Arkansas. Fallenrollment is typically 1,800 credit students, and about half of thefirst-time freshmen declare a transfer major. The Ozarks UnlimitedResources Cooperative (OUR Co-op) assists public school districts inroughly the same five-county area by providing them with sharededucational programs and services. Both institutions reside in Har-rison, population 12,000, one of the ‘‘100 Best Small Towns in America’’(Crampton, 1993).
In the Fall of 1999 the Director of Institutional Research atNorthark, the Vice President of Student Services at Northark, and theMath Facilitator from the OUR Co-op began work on a plan to providefeedback to public school teachers about performance of their gradu-ates in college. Specifically, they hoped to share information with localteachers about the success of recent high school graduates in mathcourses at Northark. Queried about their interest in such feedback,high school administrators and, especially, teachers respondedenthusiastically to the project. That Fall the Northark InstitutionalResearch Office (IR Office) analyzed high school transcript data for allMay 1999 graduates of local schools who were enrolled at Northark.
Bridging the Gap 395
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The transcript analysis focused on math courses taken in high school,primarily on factors such as the highest course completed, gradesearned, and presence or absence of math during the senior year. Twoquestions were of primary concern: (1) Do students who take collegepreparatory math courses in high school place into, and succeed in,college math courses at Northark? Stated differently, do students placeinto remediation because they didn’t take the ‘‘right’’ courses in highschool, or did they take the college preparatory courses yet still needremediation?; and, (2) Do students who come to college for a degreetake sufficient college preparatory coursework in high school?
The IR Office prepared summary reports for each school, carefullyensuring the anonymity of students, and shared the information withteachers and counselors during a late Fall Co-op meeting. The sameoffice prepared a second report after the college recorded Fall gradesand students began classes for the Spring semester. The IR Officecontinued to track this cohort of students through the summer andmailed a third report to counselors and teachers near the end ofSummer 2000.
Northark and the public school teachers continued to share infor-mation and hold discussions during the next two years. Northarkmath faculty reviewed the information released to high school per-sonnel during the first two years and began meeting with high schoolfaculty during the third year.
SAMPLE
Each Fall’s sample consisted of first-time freshmen students atNorthark who had graduated from any of the OUR Co-op secondaryschools during the previous academic year. During the first threeyears of the study, transcript data were analyzed for 623 students from22 high schools, 186 students in year one, 210 in year two, and 227 inyear three.
Each year a few students entered Northark as non-degree seekersand were not required to take a placement examination. These stu-dents were included in summary statistics of high school courses takenbut were omitted from college follow-up.
STUDY VARIABLES
The highest math course completed in high school was the primaryindependent variable in our research. The three values of this variablewere above Algebra 2, Algebra 2, or below Algebra 2. The study
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considers Geometry of lower level than Algebra 2, and courses such asAdvanced Math of higher level than Algebra 2.
Assignment of math courses listed on the transcript was usuallystraightforward but occasionally required assistance from high schoolcounselors or teachers or the OUR Co-op’s math facilitator. Table 1shows math courses, as they appeared on high school transcripts, forthe three years of the study. Courses shown in bold type were con-sidered more advanced than Algebra 2.
The study also considered students’ grades in the highest mathcourse they completed. Because most high school courses are twosemesters long, the IR Office averaged grades for both semesters usingthese conversions: A¼ 4, B¼ 3, C¼ 2, D¼ 1, and F¼ 0. For example, astudent who earned an A in semester one and B in semester two ofhigh school Geometry would show a grade of 3.5 for the course. If astudent completed only one semester of a course, the study used thatgrade.
The dependent variables in the study were college math placementand college math success. Placement refers to placement into a ‘‘col-lege-level’’ or ‘‘remedial’’ math course based on math ACT or Compasstest scores. Northark requires all first-time degree seeking students totake one of these placement tests prior to enrollment. College Algebrais the first in the sequence of college level math courses. Althoughsome certificate or Associate of Applied Science (A.A.S.) programsrequire math only as high as Intermediate Algebra, College Algebra isa requirement for Northark Associate of Arts (A.A.) and Associate ofScience (A.S.) degrees. Therefore, this study assumes courses at a levellower than College Algebra to be remedial. From lowest to highest the
TABLE 1 High School Courses
Integrated Algebra A LC MathA-School Math Integrated Algebra B Math IAdvanced Math Integrated Algebra I Math Study SkillsAlgebra A Intro. to Int. Algebra Math Technology IAlgebra A-B Business=Computer Math Math Technology IIAlgebra B Calculus MathþAlgebra C-D Applied Geometry Pace MathAlgebra Connections College Prep Geometry Practical MathAlgebra I Geometry Resource MathAlgebra II Geometry A SS Algebra IAlgebra III Geometry B SS Algebra IIAlgebra Interact A Integrated Geometry TrigonometryDSC Algebra Investigative Geometry
Bridging the Gap 397
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sequence of Northark math courses is: Basic Math, Beginning Algebra,Intermediate Algebra, and College Algebra.
Since progression to the next math class in the sequence requires agrade of at least C, as does transfer of the course, the study definedsuccess in a college math course as a grade of A, B, or C. Other possiblegrades included D, F, or W (withdrew). A few students audited a mathcourse; these students were omitted from computations of successversus failure.
ANALYSIS OF DATA
The IR Office manually entered high school transcript data for eachstudent and added placement data and other demographic data fromthe college’s student record system during the Fall semester and col-lege math courses and grades at the beginning of the Spring semester.
Analysis of data was to determine overall math placement of stu-dents, placement by highest high school math, and success in collegemath by highest math course. Another variable considered in theanalysis was the grade earned in the highest high school math class.
As a reminder, the intent of this project was to share informationabout high school coursework completed and subsequent placementand success at Northark. Northark and the OUR Co-op used thisinformation to begin dialogue between high school and college facul-ties, not to develop a predictive model of college success.
FINDINGS
Student Intent and Courses
Over the three years of the study, 623 students entered Northark fromlocal schools as first time freshmen. Fifty-seven percent of these stu-dents declared a transfer major (A.A. or A.S.), 21% pursued a two-yearA.A.S. degree, and 15% were certificate seekers; the remainder did notdeclare a major (Table 2).
Over half of the students (53%) completed Algebra 2 as their highesthigh school math course. Only 25% had completed a course moreadvanced than Algebra 2 (Table 3).
It is reasonable to assume that transfer students, those intending toearn an A.A. or A.S., would have completed a more rigorous programof study in high school and so have better placement into collegecourses. There was some truth to this, although the percentage oftransfer students who placed into college level math was still low.Table 4 shows that 33% of transfer students took a course more
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advanced than Algebra 2, compared to 25% of A.A.S. students and only4% of certificate-seeking students.
Placement
Only 34% of students in the study placed into college level math(College Algebra) upon entering Northark. The good news is that 73%of students who completed a course higher than Algebra 2 placed into
TABLE 3 Highest High School Math Course of Entering Students
Frequency Percent
Above alg2 158 25.4Alg2 329 52.8Below alg2 136 21.8Total 623 100.0
TABLE 2 Degree Intent of Entering Students
Frequency Percent
AA or AS 356 57.1AAS 130 20.9Certificate 95 15.2Degree—undeclared 26 4.2Undeclared 16 2.6Total 623 100.0
TABLE 4 Highest High School Class by Degree Intent
Highest high school class
Above alg2 Alg2 Below alg2 Total
Degree intent AA or AS 116 206 34 35632.6% 57.9% 9.6% 100.0%
AAS 33 69 28 13025.4% 53.1% 21.5% 100.0%
Certificate 4 33 58 954.2% 34.7% 61.1% 100.0%
Undeclared 5 21 16 4211.9% 50.0% 38.1% 100.0%
Total 158 329 136 62325.4% 52.8% 21.8% 100.0%
Bridging the Gap 399
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college-level math; in contrast, only 29% of those whose highest coursewas Algebra 2 placed into college level math (Table 5).
Transfer students were more likely to place into college-level math(44%) than were A.A.S. (30%) or certificate students (8%), but thedifference seems to result from the highest class taken rather thandegree intent. There was no significant difference in placement oftransfer students and A.A.S. students after controlling for the highesthigh school courses.
Placement into college math is, however, only the first step. Successis the real goal. Over the three year period students who completed acourse more advanced than Algebra 2 were much more likely thanothers to pass their first Northark math course, even when taking aremedial course. Table 6 shows success or failure of students whoenrolled in a math course during their first semester. For example, 156students completed a course higher than Algebra 2, and 114 of theseplaced into a college level math course. Eighty-six of the 114 enrolledin a math course during the fall, and 66 of these (77%) passed thecourse with an A, B, or C.
Note that 78% of students who completed a course higher thanAlgebra 2 and then enrolled in a Northark math course during the firstFall successfully completed the course, whether remedial or collegelevel; this means less time and money spent to repeat courses, and ahigher likelihood of achieving their goal in college. In contrast, only54% of students with an Algebra 2 background and 27% of studentswith less than an Algebra 2 background passed the math course theyenrolled in the first Fall. These students started their college math
TABLE 5 Math Placement by Highest High School Math
Math placement
Placed incollege level
Placed inremedialcourse Total
Highest highschool class
Above alg2 11473.1%
4226.9%
156100.0%
Alg2 94 231 32528.9% 71.1% 100.0%
Below alg2 1 128 129.8% 99.2% 100.0%
Total 209 401 61034.3% 65.7% 100.0%
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TABLE
6CollegeMath
SuccessbyHighestHighSch
oolClass
andPlacemen
t
Sem
ester1pass
fail
Grouptotal
Table
total
Passed
Did
not
pass
Audit
Cou
nt
Row
%Cou
nt
Row
%Cou
nt
Row
%Cou
nt
Cou
nt
Highest
high
school
class
Abov
ealg2
Math
placemen
tPlacedin
colleg
elevel
66
76.7%
20
23.3%
86
114
Placedin
remed
ialcourse
24
80.0%
620.0%
30
42
Group
total
90
77.6%
26
22.4%
116
156
Alg2
Math placemen
tPlacedin
colleg
elevel
40
59.7%
27
40.3%
67
94
Placedin
remed
ialcourse
90
51.4%
85
48.6%
175
231
Group
total
130
53.7%
112
46.3%
242
325
Below
alg2
Math placemen
tPlacedin
colleg
elevel
1100.0%
11
Placedin
remed
ialcourse
21
27.3%
54
70.1%
22.6%
77
128
Group
total
21
26.9%
55
70.5%
22.6
78
129
Table
total
241
55.3%
193
44.3%
2.5%
436
610
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career from one to three semesters behind, and they have stayedbehind. The opportunity gap between these students and others con-tinues to widen.
Grades
This study focused on the relationship between curriculum and Col-lege Algebra placement and success, not on the impact of high schoolgrades. Students who did what was necessary to earn a high grade inhigh school, whether in Algebra 2 or in a more advanced course, mightbe more likely to do what it takes to perform well in college. It isdifficult to separate the effect of course grade from the effect of thework ethic of students, especially with 22 diverse high school gradingpolicies.
Still, grades provide some information about the likely success ofstudents in college. The study found that:
1. High grades accompanied more advanced high school courses.Students who completed a course more advanced than Algebra 2earned an average of 2.9 on a 4.0 scale in the class, while studentswho completed only as high as Algebra 2 averaged a course gradeof 2.4.
2. High school grades seemed to make a difference in college place-ment for students whose highest high school class was Algebra 2(Table 7). Students who placed into College Algebra from Algebra 2had an average Algebra 2 grade of 2.9 on a 4.0 scale, well aboveaverage for the group of all Algebra 2 students. Students from thesame group who placed into remediation averaged 2.3. The dif-ference was significant at the alpha¼ 0.05 level. Students whocompleted a class more advanced than Algebra 2 had little dif-ference in grade average.
TABLE 7 Grades in Highest High School Class by Math Placement
Count Mean
Highesthighschoolclass
Above Math placement Placed in college level 114 2.9alg2 Placed in remedial course 41 2.7
Group total 155 2.9
Alg2 Math placement Placed in college level 93 2.9Placed in remedial course 229 2.3
Group total 322 2.4
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3. Regardless of the highest high school math taken, students whopassed College Algebra the first semester had earned a higheraverage grade in high school math than those who did not pass(Table 8).
A successful transition to college algebra seems to require morethan just good high school grades. Seventy-nine percent of studentswho earned a 3.1 or higher (on a 4.0 scale) in an advanced math courseplaced into College Algebra, compared to only 51% of Algebra 2 stu-dents who earned a similar grade. The curriculum matters.
RESULTS OF COLLABORATION
Pulling together faculty from the college and high schools proved moredifficult than anticipated. The problems stemmed from logistics, notlack of interest.
During the first two years of the project, the Director of Institu-tional Research, accompanied by the Vice President of Student Ser-vices, provided regular updates to the public school teachers duringmath workshops at the OUR Co-op. They planned a formal meetingbetween the two faculties, hosted by Northark, for the end of year two,but had to cancel due to scheduling conflicts and other complications.Because formal gatherings proved so difficult to arrange, college mathfaculty began attending the Co-op meetings in year three.
At the end of the third year of the study, the IR Director met withthe combined faculties to summarize results and offer answers to thetwo research questions. During these meetings high school teachersviewed College Algebra textbooks and course syllabi, and instructorswith experience in secondary and college-level instruction describedtheir perception of the obstacles students faced as they made the
TABLE 8 Grades in Highest High School Class by College Algebra Success
Count Mean
Highesthighschoolclass
Abovealg2
Semester 1pass fail
PassedDid not pass
6620
3.12.3
Group total 86 2.9
Alg2 Semester 1pass fail
PassedDid not pass
4026
3.32.3
Group total 66 2.9
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transition to college. In a meeting near the end of academic year2001�2002, faculty discussed two main topics:
1. measures that would encourage high school students to take amore rigorous math course curriculum, and
2. changes to create better articulation between Algebra 2 and col-lege-level math.
Some issues that affect these topics surfaced during the meetingand they, along with a summary of the discussion, follow:
Issue 1: High school and college courses often use different gradingcriteria. For example, test grades constitute the majority of the CollegeAlgebra grade at Northark, while homework makes up most of thegrade for many high school classes. Related to this issue, some highschool teachers felt pressure from their administration to ‘‘pass’’students.
Discussion: Although some teachers felt pressured to pass students,many others had already fought this battle, and apparently had won.Most of these felt that administrators would support their gradingcriteria as long as course grades were, in general, a good reflection ofstandardized test scores.
The OUR Co-op Math Facilitator proposed that the group develop astatement that suggests a more uniform grading standard with lessweight given to homework; the statement would allow the group tospeak with a united voice to area administrators.
Issue 2: High school and college courses often use different criteriafor ‘‘success.’’ Students can pass a high school course with a grade of D,but need a C in college level math to progress to the next course.
Discussion: The group did not discuss changing the definition of a‘‘passing’’ grade, but the study indicates that students who earned a Din their highest high school math course are ill-prepared for collegemath.
Issue 3: Arkansas still requires only three years of high schoolmath; many students have completed Algebra 2 by their junior year orearlier, and see no need for an additional math course during theirsenior year.
Discussion: High school and college faculty agreed that studentsneed a reason to take more math, and more rigorous math, duringtheir senior year. Northark already offers dual credit courses such asCollege Algebra to high school students via a well-used distance edu-cation program. Some high schools, however, prefer to offer dual creditcourses from their campus using qualified high school teachers. Thisoption was discontinued because of problems with on-site dual credit
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courses in the past, but Northark is now working with area highschools to redevelop the program.
Northark personnel suggested giving the Compass test during thesophomore or junior year so students will know if they are on track toenroll in college-level math. Also, many participants felt that the stateshould require students to complete four years of high school math.While this is a logical step, if schools continue to split a one-yearcourse such as Algebra 1 into two one-year courses (Algebra A and B),then the change will be pointless.
Issue 4: The senior year. Math is not the only problem during senioryear, in which high school students may be in class only a few hoursdaily.
Discussion: A required fourth year of math and enhanced dualcredit opportunities may give students reasons to stay in the class-room. Schools can begin to implement recommendations such as thosefrom the National Commission on the High School Senior Year to helpstudents remain engaged with school.
More problems were identified than were solved during the meet-ing. The OUR Co-op Math Facilitator hopes to develop a policystatement from the combined faculties to be given to administrators,and has asked the IR Director to present a summary of this project tohigh school administrators and superintendents. Northark hopes toprovide at least one College Algebra textbook for each high schoolmath teacher, and to allow high school faculty to take the math portionof the Compass test to gain a better idea of problems students facewith placement tests.
CONCLUSIONS
1. Do students who take college preparatory math courses in highschool place into and succeed in college math courses at Northark?Yes, as long as ‘‘college preparatory’’ is defined as a course moreadvanced than Algebra 2.
2. Do students who come to college for a degree take sufficient collegepreparatory coursework in high school?No. Only 25% of students tracked during the three years of thisstudy had completed courses more advanced than Algebra 2.
Recommendations
There is no easy solution to the problem of high remediation and lowachievement as students make the transition to college math; theserecommendations are offered as a starting point.
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� Just offering more rigorous math courses won’t solve the problem—students must actually take the courses!
� Data such as these should be publicized to teachers, counselors,parents, school boards, and public school administrators. It is pos-sible these interested parties do not realize the consequences of sucha broad, but weak, math curriculum.
� High school administrators, counselors, and teachers should starttalking to students (and parents) in early grades about college.Many students will plan to attend college, and prepare for it, if weencourage them early on.
� High schools should find an alternative to tracking—less rigorousmath courses, at least in our area, do not prepare students foranything except to receive a high school diploma.
� High school students should receive placement testing during theirsophomore or junior year; this can provide concrete evidence tostudents that they need more math.
� High schools must find ways to keep students in relevant classesduring the senior year.
� Colleges and public schools must communicate and work together.Although we are distinct, we depend on each other.
Summary
The data indicate that a fourth year of rigorous high school math,something more advanced than Algebra 2, greatly increased thelikelihood that a student would place into college level math. Perhapsas important, students who completed a post-Algebra 2 course weremore likely than others to succeed in college math, even if they placedinto a remedial course. Students who took a rigorous math curriculumin high school were more likely to enter college at the appropriate levelor to progress to college level after a semester in remediation. Stu-dents who lacked a rigorous high school math course often startedcollege one to three math courses (thus semesters) behind and thenstayed behind because of their high failure rate in the remedialcourses.
Remediation rates for college-going students continue to soar, yetnational studies show that a high quality high school curriculum caneliminate much of the need for remediation. The trouble with nationalor regional studies is that the results, even if they filter down to thelocal level, often have little effect on what happens to individual stu-dents in individual schools. The purpose of this project was to bringhigh school and college math faculty together to observe closely what
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happens as local students make the transition from secondary tohigher education. Although we are only beginning the dialogue, col-laboration between the two groups might be the catalyst that bringsneeded change to our area of Arkansas, then to the entire state.
REFERENCES
Adelman, C. (1996, October 4). The truth about remedial work. The Chronicle of HigherEducation, p. A56.
Adelman, C. (1999). Answers in the tool box: Academic intensity, attendance patterns,and bachelor’s degree attainment. Washington, DC: U.S. Government Printing Office.
Chronicle of Higher Education. (2001, August). Almanac Issue.Crampton, N. (1993). The 100 best small towns in America. New York: Prentice Hall.Family income by educational attainment of householder, 1956 to 1999 (2000,
December). Postsecondary Education Opportunity, 102, 1�4.Harrell, R. (2001, April). Annual report on first-year student remediation. Student
success: Graduation & retention in Arkansas. Paper presented at the meeting of theArkansas Higher Education Coordinating Board, Little Rock, AR.
Harrell, R. (2001). Student enrollment fall 2001. Retrieved March 3, 2003 fromArkansas Department of Higher Education website: http:==www.arkansashighered.com=enrollment-2001.html
Jago, C. (2000). It’s the curriculum, stupid. American School Board Journal, 187(4), 66,68.
Johnston, R., & Hardin, L. (2001). Student success: Graduation & retention in Arkansas.Little Rock, AR: Arkansas Dept of Higher Education.
Measuring up 2000: The state by state report card for higher education. (2000). TheNational Center for Public Policy and Higher Education. [On-line]. Available:http:==measuringup2000.highereducation.org=reporthome.htm
Mortenson, T. (2002, February). Higher education as a private and social investment.Paper presented at the meeting of the Key Bank Financing Conference 2002,Orlando, FL.
The lost opportunity of senior year: Finding a better way. Summary of results, retrievedMarch 3, 2003 from National Commission on the High School Senior Year website:http:==www.commissiononthesenioryear.org=Report=CommissionSummary2.pdf
U.S. Department of Education, National Center for Education Statistics. (2000). Thecondition of education 2000 (NCES Publication No. 2000-602). Washington, DC: U.S.Government Printing Office.
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20 Notices of the AMs VoluMe 56, NuMber 1
Is the Sky Still Falling?David M. Bressoud
In the 1998 Notices article “The Sky is Falling” [4], Garfunkel and Young drew attention to the alarming decrease in the number of stu-dents who study mathematics in college. In their words, “Our profession is in desperate
trouble—immediate and present danger [...] If something is not done soon, we will see math-ematics department faculties decimated and an already dismal job market completely collapse.” In the past ten years the situation seems to have reversed. The mathematical community is not in the desperate straits that Garfunkel and Young predicted. Yet, as this article will show, the situa-tion is far from healthy, and in many respects we are worse off now than we were in 1995. Today we teach a smaller percentage of the total enrollment than ever before. The growth that has occurred has been entirely within our research universities, and there it can be explained by a short-term increase in the number of engineering students. This article concludes with three action items that the math-ematical community needs to undertake if we are to reverse this decline.
Garfunkel and Young’s argument rested on data from the Conference Board of the Mathematical Sciences (CBMS) showing a drop in enrollments from 1985 to 1995. As Table 1 shows, the situa-tion in 1995 looked far worse than it does today. Enrollment in precollege (remedial) mathematics has continued to decline at 4-year colleges.1 For all other categories of courses,2 enrollments are up
over the 1995 numbers by between 9% and 17%. While we are still well below the 1985 numbers for courses at the level of calculus and above, whatever was going wrong in the early 1990s seems to have been corrected.
But if we compare the number of students studying mathematics to the number of students enrolled in our 4-year undergraduate programs, we see that mathematics has been accounting for an ever-decreasing slice of the pie. The figures for 1995 were bad, but the percentages for 2005 are considerably worse (see Table 2).
These percentages should be alarming. The true situation is revealed to be even more discouraging once we unpack these numbers and look at what is happening in individual courses and at specific types of institutions. Because of its central role in the undergraduate curriculum, I will focus on calculus.
Calculus in High SchoolIn the spring of 1985, 46,000 students took the Advanced Placement Calculus exam. In spring 2008, the number was 292,000. By 2009, it will be well over 300,000. In fact, the number of AP Calculus exams given each year has grown steadily over the past decade at an average rate of over 7% per year with no sign yet that it is approaching its inflection point (see Figure 1). AP Calculus exam takers are only a piece of the broader population of students who study calculus while in high school, a population that includes those who take an AP Calculus course but not the exam as well as those in the International Baccalaureate program, dual enrollment programs, registration in 2- or 4-year college calculus classes, and the many students who are given a soft introduction to calculus while in high school in the hope of easing the transition to college calculus. Based on the NELS study from spring 2004 [3], the NAEP transcript study from 2005 [12], and the growth of AP Calculus since then, it is safe to conclude that we have reached the point where each year over half a million high school students study calculus.
David M. Bressoud is DeWitt Wallace Professor of Math-ematics at Macalester College and president elect of the Mathematical Association of America. His email address is [email protected] precollege or remedial mathematics is taught at 2-year colleges where it now accounts for 61% of all mathematics taught at these colleges.2Introductory level includes College Algebra, Precalculus, and Math for Liberal Arts. Calculus level is Calculus I through Differential Equations, Linear Algebra, and Dis-crete Math. Advanced is everything above calculus level including Introduction to Proofs. Statistics courses are not included in these numbers.
JANuAry 2009 Notices of the AMs 21
Most of the students who study calculus in high school do not receive college credit for this course. Morgan [8] estimates that about half of the stu-dents who take the AP Calculus exam are entitled to and choose to use credit for Calculus I. Perhaps another 30,000 receive college credit via dual enrollment, IB, or enrollment in a college class. A reasonable estimate is that between 150,000 and 200,000 students arrive at college each fall bring-ing with them credit for calculus. That suggests that we should be seeing dramatically increasing numbers of students taking Calculus II in the fall term. As Table 3 shows, this is not the case. In fact, Calculus II enrollments in the fall term actually dropped over the period 2000–05.
What about the other 300,000–350,000 students who took calculus but not for college credit? One would hope that the increasing numbers of these students would translate into increasing numbers of students taking calculus in college. But combin-ing all mainstream Calculus I classes in all 2- and 4-year colleges in the United States, fall enrollments have been stuck at very close to 250,000 over the past quarter century.
Calculus in CollegeAt least we have seen some increase in the Cal-culus I, III, and IV enrollments over the period 2000–05. In fact, even that is less robust than it seems. When we break down calculus enrollments
by type of institution,3 we see that the growth is occurring entirely at the research universities (see Figures 2–4).
For all levels of college calculus, the increase since 1995 is entirely within the research univer-sities. Everywhere else, enrollment has declined. There is a distinctive pattern of enrollments across all levels of calculus that occurred at the research universities and at no other type of institution: a five-year decline from 1990 to 1995 followed by steady growth. This pattern can be explained by the fact that most large research universities have large engineering programs. If we consider the number of incoming freshmen who intend to major in engineering (Figure 5 and Table 4), we see that it also decreased from 1990 to 1995, then grew. The scatterplot in Figure 6 shows a high cor-relation (correlation coefficient of 0.99) between the number of entering freshmen who intend to major in engineering and the total number of students in research universities each fall who enroll in any level of calculus. The downturn at the end of the graph in Figure 5 suggests that the 2005 CBMS numbers may be overly optimistic. As Table 4 shows, the number of students who intend to major in engineering began a steady decrease following a record large number in 2004.
It is interesting to compare the number of intended majors in engineering with those in the other STEM (science, technology, engineering,
3The CBMS categories of 4-year institutions are based on the highest degree offered in mathematics: Ph.D., M.A., or B.A. The labels “research university”, “comprehensive
1985 1990 1995 2000 2005precollege level 251 261 222 219 201introductory level 593 592 613 723 706calculus level 637 647 538 570 587advanced 138 119 96 102 112
1985 1990 1995 2000 2005precollege level 3.25% 3.04% 2.53% 2.34% 1.83%introductory level 7.69% 6.90% 6.99% 7.72% 6.42%calculus level 8.26% 7.54% 6.14% 6.09% 5.34%advanced 1.79% 1.39% 1.09% 1.09% 1.02%
1985* 1990 1995 2000 2005Calculus I 217 201 192 192 201Calculus II 95 88 83 87 85Calculus III & IV 90 84 62 73 74
Table 1. Mathematics enrollments (thousands) for fall term at 4-year colleges and universities in the United States. Sources: [1, 5–7].
Table 2. Mathematics enrollments at 4-year colleges as a percentage of total number of students enrolled in fall term. Sources: [1, 5–7, 13].
Table 3. Mainstream calculus enrollments (thousands for fall term in 4-year colleges). *1985 breakdown is estimate based on total number of students in all mainstream calculus classes. Sources: [1, 5–7, 13].
university”, and “undergraduate college” are substituted as descriptive of the general type of institution and to clarify that the categorization is by type of institution.
22 Notices of the AMs VoluMe 56, NuMber 1
mathematics) disciplines: the biological sciences in Figure 7 and the physical sciences (including mathematics4) in Figure 8.
ConclusionsWe have seen growth in enrollments in mathemat-ics courses over the past ten years, but that growth is well below the rate of increase in total enroll-ments. The only place where it has been robust has been where it is tied to the increase in engineering
majors, a phenomenon that appears to be cyclical and has now entered a downturn.
The mathematical community needs to look at what it can do to strengthen enrollments. One solu-tion is to get a lot more high school students to plan careers in engineer-ing. It would be interesting to know what caused the reversal in engineer-ing enrollments in the mid-1990s. These projections of intent to major in engineering were measured during freshman orientation, and thus the increase after 1995 was the result of something that happened in high school. What role did the introduction and widespread acceptance of graph-ing calculators and reform teaching methods within high schools have on the increased interest in and will-ingness to pursue highly technical majors? What is causing the current downturn in interest in engineering?
Engineering has served us well, but there is no reason why the fate of mathematics should be so depen-dent on just this discipline. The key to getting students into our advanced courses is to first get them into first-year courses that teach solid math-ematics and pique their interest to continue in mathematics. This does not have to be a course tied to the engineering curriculum. Neverthe-less, calculus is at the heart of the mathematics curriculum, and we must begin by taking a serious look at what is happening in college calculus and how well it articulates with the experiences that today’s students have in high school. This is the basis for my first two recommendations.
Recommendation 1: We need to un-derstand what happens in college to students who study calculus in high
school.
The half million students who study calculus in high school are a reasonable approximation of the top 15% of all high school graduates. They should be swelling the ranks of the students taking cal-culus- and advanced-level mathematics. We need a better understanding of what happens to these stu-dents after they enter college. For the 150,000 to 200,000 who arrive with and use credit for calculus taken in high school, how many continue to pursue mathematics and how well do they succeed? What happens to the other 300,000 to 350,000? For all of these students, what are the programs that most
4The number of freshmen intending to major in math-ematics dropped from 1.1% in 1985 to 0.5% in 2000. It has since grown to 0.8%, approximately the current percent-age of graduates who earn majors in mathematics.
Figure 1. Fall enrollments in mainstream Calculus I and number of AP Calculus exams (thousands). Sources [1, 2, 5–7, 11].
Figure 2. Fall enrollments in mainstream Calculus I by type of institution (thousands). Sources: [1, 5–7].
JANuAry 2009 Notices of the AMs 23
effectively engage them, preparing and encouraging them into the fur-ther study of mathematics?
Recommendation 2: We need to know more about the preparation of the students who take calculus in college and what they need in order to suc-ceed once they get to our classes.
We must have a better sense of who these students are who sit in our college calculus classes. What is the preparation that has gotten them to this point? How can we modify our courses so as to capitalize on the strengths and correct the weaknesses that these students bring? The an-swers to these questions will neces-sarily be local, highly dependent on the nature of a given college or uni-versity, but the entire mathematical community should be able to identify commonalities among similar types of institutions. The entire community should also promote programmatic and course structures that are par-ticularly effective for each of the dif-ferent populations we encounter.
Recommendation 3: Mainstream cal-culus should not be the only entry to good college-level mathematics.
The department of mathematics should be at the core of its college or university, interacting with every other department and working col-laboratively to develop courses that meet the needs of each group of stu-dents. These should be courses that involve real mathematics and that open the way to the further, deeper study of mathematics. This convic-tion should be part of the vision of every department of mathematics.
I look with longing at those 120,000 prospective biological science majors coming in each year. We need courses that are attractive to them, courses that give them the tools from lin-ear algebra that they will need for sophisticated statistical modeling, courses that enable them to read and write differential equations and turn them into computer simulations. We are not going to be able to convince the biologists that their students need to take more of the courses that we have created for the engineers, nor is it enough to take an engineering course and throw in some biological examples. These courses must be designed from the ground
up in collaboration with biologists. Many colleges and universities have begun this process. See, for example, Math & Bio: 2010 [14]. Doing this for biol-ogy is just the beginning of what should be a broad program of outreach and development.
The surge in engineering enrollments since 1995 coupled with the growth in physical science enrollments over the past five years has given us
Figure 3. Fall enrollments in mainstream Calculus II and number of AP Calculus exams (thousands). Sources: [1, 2, 5–7].
Figure 4. Fall enrollments in mainstream Calculus III & IV and number of AP Calculus exams (thousands). Sources: [1, 2, 5–7].
24 Notices of the AMs VoluMe 56, NuMber 1
19
85
19
90
19
95
2
00
0
20
05
15
0
16
0
17
0
18
0
19
0
20
0
21
0
22
0
23
0
24
0
10
0
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110
11
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12
0
total fall calculus enrollment (thousands)
pro
spec
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e en
gin
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san
ds)
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00
140,0
00
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Pro
spec
tiv
e B
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al S
cien
ce M
ajors
Fig
ure
6. N
um
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of
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ure
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: [9, 1
0].
JANuAry 2009 Notices of the AMs 25
a reprieve. Yet, unless we address fundamental weaknesses, the long-term prognosis for the health of undergraduate mathematics is not good. I am still optimistic. Many talented people are working hard to improve the undergraduate program in mathematics. With a better of sense of where we are and widespread dissemination of what works, we can build a foundation for the future.
References [1] Donald J. Albers, Don O. Loftsgaarden, Don-
ald C. Rung, and Ann E. Watkins, Statistical Abstract of Undergraduate Programs in the Mathematical Sciences and Computer Science in the United States: 1990–91 CBMS Survey, Number 23 in MAA Notes, Mathematical Association of America, Washington, DC, 1992. http://www.ams.org/cbms/cbms1990.html.
[2] College Board, AP report to the nation, New York, NY, 2004–2007. http://professionals. collegeboard.com/data-reports-research/ap/nation.
[3] Ben Dalton, Steven J. Ingels, Jane Downing, Rob-ert Bozick, and Jeffrey Owings, Advanced Math-ematics and Science Coursetaking in the Spring High School Senior Classes of 1982, 1992, and 2004: Statisti-cal Analysis Report, Number 2007-312, National Cen-ter for Education Statistics, U.S. Department of Educa-tion, Washington, DC, 2007. http://nces.ed.gov/ pubsearch/pubsinfo.asp?pubid=2007312.
[4] Solomon A. Garfunkel and Gail S. Young, The sky is falling, Notices of the AMS, 45 (1998), 256–257.
[5] Don O. Loftsgaarden, Donald C. Rung, and Ann E. Watkins, Statistical Abstract of Undergraduate Pro-grams in the Mathematical Sciences in the United States: Fall 1995 CBMS Survey, Number 2 in MAA Reports, Mathematical Association of America, Wash-ington, DC, 1997. http://www.ams.org/cbms/cbms1995.html.
[6] David J. Lutzer, James W. Maxwell, and Stephen B. Rodi, Statistical Abstract of Undergraduate Programs in the Mathematical Sciences in the United States: Fall 2000 CBMS Survey, American Mathematical Society, Providence, RI, 2002. http://www.ams.org/cbms/cbms2000.html.
[7] David J. Lutzer, Stephen B. Rodi, Ellen E. Kirk-man, and James W. Maxwell, Statistical Abstract of Undergraduate Programs in the Mathematical Sciences in the United States: Fall 2005 CBMS Survey, American Mathematical Society, Providence, RI, 2007. http://www.ams.org/cbms/cbms2005.html.
[8] Karen Christman Morgan, The use of AP examina-tion grades by students in college, preprint.
[9] John H. Pryor, The American freshman: Forty year trends, ACE Research Reports, Higher Education Re-search Institute, UCLA, Los Angeles, CA, 2007.
[10] John H. Pryor, Sylvia Hurtado, Jessica Shark-ness, and William S. Korn, The American freshman: National norms for 2007, ACE Research Reports, Higher Education Research Institute, UCLA, Los An-geles, CA, 2007.
[11] Larry Riddle, personal communication of record maintained by AP Calculus Chief Readers of the total number of exams taken each year.
[12] Carolyn Shettle, Shep Roey, Joy Mordica, Robert Perkins, Christine Nord, Jelena Teodo-rovic, Janis Brown, Marsha Lyons, Chris Aver-ett, and David Kastberg, America’s High School Graduates: Results from the 2005 NAEP High School Transcript Study, Number 2007-467, National Center for Education Statistics, U.S. Department of Educa-tion, Washington, DC, 2007. http://nces.ed.gov/ nationsreportcard/pubs/studies/2007467.asp.
[13] Thomas D. Snyder, Sally A. Dillow, and Char-lene M. Hoffman, Digest of Education Statistics: 2007, Number 2008-022, National Center for Edu-cation Statistics, U.S. Department of Education, Washington, DC, 2008. http://nces.ed.gov/ programs/digest/.
[14] Lynn Arthur Steen, editor, Math & Bio 2010: Link-ing Undergraduate Disciplines, Mathematical Associa-tion of America, Washington, DC, 2005.
#prospectiveengineers
%biologicalsciences
#biologicalsciences
#physicalsciences
#physicalsciencesyear
4-year freshman enrollment
%engineering
1985 1,067,928 11.0% 117,000 4.6% 49,000 3.3% 35,0001986 1,023,762 10.2% 104,000 4.6% 47,000 3.0% 31,0001987 1,031,968 9.4% 97,000 4.4% 45,000 2.7% 28,0001988 1,076,036 8.7% 94,000 4.4% 47,000 2.7% 29,0001989 1,028,143 9.9% 102,000 4.5% 46,000 2.8% 29,0001990 1,010,548 9.7% 98,000 4.8% 49,000 2.8% 28,0001991 1,024,976 10.8% 111,000 5.7% 58,000 2.9% 30,0001992 1,060,087 10.0% 106,000 6.5% 69,000 3.1% 33,0001993 996,690 10.0% 100,000 7.1% 71,000 3.3% 33,0001994 1,017,725 8.8% 90,000 7.9% 80,000 2.9% 30,0001995 1,024,550 8.1% 83,000 8.3% 85,000 3.0% 31,0001996 1,076,035 9.7% 104,000 8.2% 88,000 2.8% 30,0001997 1,054,500 9.7% 102,000 8.0% 84,000 2.8% 30,0001998 1,066,679 8.2% 87,000 7.1% 76,000 2.5% 27,0001999 1,098,833 9.0% 99,000 7.2% 79,000 2.5% 27,0002000 1,101,817 8.7% 96,000 6.8% 75,000 2.5% 28,0002001 1,204,240 9.1% 110,000 6.9% 83,000 2.6% 31,0002002 1,234,968 9.5% 117,000 7.2% 89,000 2.7% 33,0002003 1,196,089 9.3% 111,000 7.3% 87,000 2.7% 32,0002004 1,258,333 9.6% 121,000 7.7% 97,000 3.0% 38,0002005 1,298,093 8.4% 109,000 7.6% 99,000 3.1% 40,0002006 1,320,824 8.0% 106,000 8.3% 110,000 3.1% 41,0002007 1,354,958 7.5% 102,000 8.6% 117,000 3.1% 42,000
Table 4. Number of freshmen in 4-year undergraduate programs who intend to major in engineering. Sources: [9, 10].
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Student Preferences, Satisfaction, and Perceived Learning in an Online Mathematics Class
Julie Glass
Department of Mathematics and Computer Science California State University, East Bay
Hayward, CA 94542 USA [email protected]
Valerie Sue California State University, East Bay
Hayward, CA 94542 USA [email protected]
Abstract
This study analyzes student preference, satisfaction and perceived learning in an online college mathematics course for business majors. Using a combination of active and passive learning objects, the online course was developed to investigate the instructional strategies students use the most, prefer and believe impact their learning. Students answered weekly surveys about the course. They were asked to report their usage of the learning objects and to reflect on their interactions with the material and with each other. They were also asked to assess the impact that various learning objects had on their learning and on their satisfaction with the course and with the material. Of the learning objects investigated, homework emerged as the factor students preferred and used the most, and that they felt had the greatest impact on their learning. Participation in online discussions did not surface as a favored or significant factor in the students’ learning. This work is aimed at informing best practices for increasing student engagement, and thus learning, in online mathematics and other similar courses.
Keywords: Online learning, Learning Objects, Active Learning, Mathematics, Survey Research
Introduction
The Internet has brought about a paradigm shift in the way professors teach and students learn. Online courses, an experimental concept less than a decade ago, have become de rigueur for postsecondary institutions wishing to maintain a presence at the forefront of educational innovation. Research about online teaching and learning has, however, struggled to keep pace with the rapid development of the field. Recently, the focus has shifted from questions surrounding whether online education is effective to how best to achieve important student learning outcomes in online environments.
This study analyzes student preference, satisfaction and perceived learning in an online mathematics course. Students answered weekly surveys about the course. They were asked to reflect on their interactions with the material, each other and the professor as well as on the impact that various learning objects had on their learning and on their engagement in the course. This work is aimed at informing best practices for organizing and presenting course material in online mathematics and related courses.
Literature Survey
The Internet has provided a new mechanism for connecting teachers and students; however, distance education is hardly a new concept. Saba (2005) notes that distance learning can be traced back to the 1800s; technological developments, including radio in the 1920s, television in the 1950s, and the use of the Internet by civilian organizations in the mid-1980s, have contributed to moving distance education from a fringe activity to a central focus in American higher education. Whether the method is termed
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distance education, distributed learning, e-learning or online education, one consistent goal in the study of these methods of bringing instructors and learners together has been to determine optimal strategies for enhancing the student learning experience.
One avenue of research activity that has received attention across disciplinary boundaries is focused on the notion of active learning. Active learning is fostered when instructional methods engage students in the learning process (Bonwell & Eison, 1991). Active learning takes place when instructors ask students to reflect on what students are doing and participate in meaningful learning activities. In an online learning context, this may take the form of journal entries or discussion board postings as well as traditional homework assignments or simulation exercises. In an extensive review of the literature surrounding active learning, Prince (2004) discovered substantial empirical support for the assertion that active learning can significantly improve recall of information and substantially contributes to student engagement. Active learning strategies have been shown to lead not only to greater retention of course material but also to increased satisfaction in online courses (Sahin, 2007).
The literature regarding student satisfaction in online courses is less clear cut than the active learning line of studies. While some researchers have found that learner-centered activities are central to student satisfaction in online courses (Ellis & Cohen, 2005), Cuthrell and Lyon’s (2007) recent investigation discovered that students preferred a mix of instructional strategies that incorporated active and passive modes of instruction. Other factors that have been shown to be related to student satisfaction in online courses are presence (social, cognitive and teaching) (Pelz, 2004), community (Sahin, 2007) and frequent feedback and assessment (Swan, 2003).
In a study of non-posting (i.e., lurking) discussion board behavior among students in online classes, Dennen (2008) found that about half of the students felt that they learned through online discussions (both posting and reading messages); students who reported that they participated in discussion only to meet course requirements and those who focused more on posting rather than reading messages had less positive impressions of the discussions’ impact on their learning.
The nomenclature of learning objects (LOs) provides a useful framework for discussing the Web-based multimedia systems used to deliver instructional content in online courses. Learning objects have engendered considerable debate as of late (Bennett & McGee, 2005; Friesen, 2003; Parrish, 2004) and definitions vary widely (Liber, 2005), however, the fervor with which supporters and detractors continue to engage in debate over both the explication of the concept and its utility for higher education is an indication of the resilience of the concept.
As defined by Hodgins (2000), LOs are small, reusable instructional components designed to achieve specific learning objectives that are delivered via the Internet. Hodgins (2000) compared LOs to LEGO building blocks; that is, individual course components that can be easily added, removed or replaced, making course content highly adaptable. Wiley (2002) broadened the concept by defining LOs as any digital resource that can be reused to support learning. The definition of LOs used in the present research follows loosely from Hodgins’ (2000) original definition.
With the literature concerning student preferences, satisfaction and perceived learning as a base (with particular attention being given to active learning strategies), and with the taxonomy of learning objects as a framework, this research endeavored to investigate the LOs that students preferred, used the most and were the most satisfied with as well as the LOs that they believed had the most impact on their learning.
The course and the university
The vehicle for this study was a quarter-long (ten weeks) online mathematics course for Business and Social Science students at California State University, East Bay (CSUEB). CSUEB is a mid-sized comprehensive, public urban university in the San Francisco Bay Area. The student population is highly varied in age, ethnicity and socioeconomic status (see participants section). The course has a prerequisite of college algebra and is required for all business majors and for entry into the MBA program. The course consisted of ten learning modules consisting of two lectures and a series of online assignments. Students were required to complete one module each week for which all material was made available at midnight on the first day of the week. The course material included: functions and graphs; exponential and logarithmic functions; mathematics of accounting and finance; matrices and
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systems of equations; linear programming (a geometric approach); and an introduction to differential and integral calculus with applications to business and social sciences. Grades were based on a total of 1000 points as shown in Table 1 below and the grades were assigned based upon a standard points-to-grades scheme as shown in Table 2. Table 1: Point distribution for Learning Objects
LO Points
Homework
Discussion
Quizzes
Midterm
Final Exam
Total Possible
240 (12 points each)
60
200 (20 points each)
200
300
1000
Table 2: Points to Grade Scheme
Total Pts Earned
Grade Assigned
Total Pts Earned
Grade Assigned
930 – 1000
900 – 929
870 – 899
830 – 869
800 – 829
A
A-
B+
B
B-
770 – 799
730 – 769
700 – 729
670 – 699
600 – 669
< 600
C+
C
C-
D+
D
F
The course was delivered via the Blackboard (Bb) Course Management System (CMS). All homework, quizzes and examinations were completed on a publisher-supported course shell, Course Compass, utilizing an online homework service, My Math Lab (CC/MML). All course requirements were completed totally online except the final exam which students were required to take in person. The instructor was present at the final exam, however all other content was completed without a proctor present. A detailed table of activities and deadlines was provided to students at the beginning of the quarter. The course was structured so as to require students to work regularly on the material. The instructor was available to answer questions online and in person via online and face-to-face office hours as well as discussion boards and via e-mail.
Learning Objects
The primary focus for this study was usage and perceived impact on learning of the LOs as described in Table 3. Figure 1 illustrates the connections between each of the LOs and satisfaction and learning. The course included the following required components: weekly homework, discussion, quizzes, one midterm examination and a final examination. It should be noted that there was some overlap between the LOs (Table 3) and the required components of the course. This is an obvious result of the fact that some LOs are needed to simply convey information while others involve active participation on the part of the student (e.g. homework, quizzes, etc.) Moreover, in any valid course design, one would expect required components to be a mode of content delivery, i.e. an integral part of the learning experience
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Table 3: Description of Learning Objects
Learning Object
Active/Passive
Required/Optional
Description
PowerPoint
Passive
Optional
Two weekly sets of PowerPoint slides which were also embedded in the video lectures and were available for printing and review on the course Bb site.
Text
Passive
Optional
Students were able to purchase a hard copy text or view an e-text on the CC/MML course site. Specific examples, “matched problems,” and “look in the book” exercises were referenced in the video lectures. Note that the text is classified as passive because that is generally the manner in which students utilize the text. The authors acknowledge that active utilization of the text is possible and desirable.
Video Lectures
Passive
Optional
Two weekly media-enhanced lectures created using Microsoft Acustudio. Lectures included head and shoulder video of the instructor, audio, PowerPoint slides and a white board feature (“examples by hand”). See Figure 2.
Homework
Active
Required
Two required homework assignments each week. All homework was done on the publisher supported site CC/MML. While doing homework, extensive worked examples (generated by MML) and “hints” are available. See Figure 3.
Discussions
Active
Required & Optional
Students were required to respond weekly to instructor-provided prompts designed to encourage higher level thinking about the weekly content. Optional discussion boards were available for general and mathematical questions and comments.
Quizzes Active
Required
Required weekly quizzes which were completed on the CC/MML site.
Methods
The data for this project were collected via a series of online surveys. The first survey of the quarter gathered general demographic information, data related to learning styles and information about math attitudes. The weekly surveys, beginning in Week 2 of the course, were brief and focused on the students’ activity during the week, related to each of the LOs. Students were asked whether they used each of the LOs and how much they felt that each one contributed to their learning of the week’s course material. The longer, final survey of the term allowed the students to rate each LO and to evaluate the course overall. This data collection process was designed to place non-grade-related data and assessments outside the domain of the course. The survey data were supplemented with student grades and course component utilization statistics collected from Course Compass.
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Figure 1. LO Interaction with Student Satisfaction and Perceived Impact on Learning
Figure 2. Screenshot of Lecture
Participants
Table 4 provides participant demographics for the course. A total of 55 students consented to participate in the research. Women were the majority of the sample, accounting for three-quarters of the participants; most were juniors or seniors and about a third were graduate students. The wide age range
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(19 to 47-years-old) and somewhat high mean age of 27.8 is typical for this university, where the campus-wide mean age is 30-years-old.
Figure 3. Screenshot of Homework Module Table 4. Demographic Profile of Research Participants
Characteristic Frequency (percent)
Gender Male Female
14 (25.5%) 41 (74.5%)
Class level Freshman/Sophomore Junior Senior Graduate student
2 (3.6%) 21 (38.2%) 15 (27.3%) 17 (30.9%)
Major Undergraduate Business MBA Other
42 (76.4%) 10 (18.2%) 3 (5.5%)
Age Range Mean Median Mode Standard deviation
19 – 47 27.8 20 7.0
The students reported working an average of 31.7 hours per week at a job or internship and 82% had taken at least one other online class. When asked why they signed up for this particular online course, “flexibility” and “to accommodate work schedules” were the two most popular reasons.
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Results
Preferences. To establish a baseline measure of preferences for various LOs, students were asked at the beginning of the quarter to report how much they liked or disliked a variety of teaching methods. The results are presented in Table 5. The clear preference for practice exercises and low rating of online discussions among these online students foretells the usage and satisfaction results that were subsequently discovered.
Table 5. Student Learning Preferences
Method
N
Mean (1=dislike very much, 5=like very much)
SD
Practice exercises 55 4.20 .78
Video lectures 55 4.00 .97
One-on-one w/instructor (online) 55 3.71 .81
Online discussions 55 3.36 1.16
Utilization. Every week, the students were asked to report whether they had used each LO and then to indicate how much each LO contributed to their learning of the week’s course material. Figure 4 provides a percent summary of utilization feedback. Percent utilization was calculated as (# utilizing LO / total respondents) x 100. All survey questions were optional; therefore, sample sizes for each question and across surveys varied. For example, the smallest sample size represented by the data in Figure 4 is 47 and the largest is 55. Week 6 was midterm week; therefore, there was no quiz. Also during Week 6, the discussion question, rather than addressing specific course content, asked that each student reflect on the course so far, resulting in a spike in participation.
Figure 4. Learning Object Utilization During the Course
It should be noted that the overlap between required components of the course such as homework, quizzes and discussion participation, and those LOs that are non-participatory and optional such as text,
No quiz week
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PowerPoint slides, and lectures, should have an impact on reported usage. Homework emerged as the LO that students reported using most; this was remarkably consistent throughout the quarter. The low utilization was in Week 5 when 96% of the students surveyed said that they did the homework; the highest utilization was in Week 9 when 100% of the respondents said they did the homework. Participation in the required weekly quizzes was consistently quite high (range = 88% - 96%, overall mean = 89%). Fewer students reported reading the text (range = 65% - 78%, overall mean = 70%) and PowerPoint slides (range = 53% - 65%, overall mean = 58%) but utilization of these LOs was fairly stable over time as well. There was more variation in reports of watching the video lectures (range = 46% - 73%, overall mean = 56%), and participating in Blackboard discussions (range = 53% - 90%, overall mean= 68%)
Course Compass afforded the opportunity to track the amount of time that students spent on homework. Figure 5 shows the mean time spent doing homework on Course Compass throughout the course. The first homework assignment of the course required students to simply report that they had successfully logged in to the Course Compass site (which they had to do to have access to the homework assignment) thus resulting in an average of 43 seconds spent on that homework assignment. As the course progressed and the homework became more challenging, time spent on homework increased dramatically; homework 8 had the highest mean time of almost two-and-a-half hours. It should be noted that this data represents the amount of time that students were logged on to the homework site; clearly, it is not possible to know whether they were actively working homework problems during the entire time that they were on the Web site. In addition, students were encouraged to print out the homework assignments, work offline, and then log in to enter their responses. Thus, the time spent-data from CC/MML could, in fact, be higher or lower than actual time spent working with the material.
Course Compass also recorded how much time students spent on quizzes; since the quizzes were timed, however, the “time spent” data was deemed not relevant for this study.
Figure 5. Mean “Time Spent” on Homework
Contribution to Learning. Along with reporting whether they had used each of the LOs, students indicated how much they felt that each one had contributed to their learning of the week’s course material. These questions were measured on a 1-to-5 point scale where 1 meant that the LO made no contribution to learning and 5 meant that the LO contributed a lot to the learning of that week’s material. Figures 6 and 7 present the mean weekly ratings for each LO; Figure 6 shows the averages for the passive LOs: lecture, text and PowerPoint slides; Figure 7 displays the averages for the active LOs: homework, quizzes and discussions. When presented this way, it is clear to see that students perceived the passive LOs to have varying contributions to their learning during the course; in week 2, for example, the PowerPoint had the greatest mean and this value then declines, spikes, and dips again near the end
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of the quarter. The lecture shows the opposite pattern, and the means for all three passive LOs converge in week 6.
Figure 6. Contribution of Passive LOs to Perceived Learning
Figure 7. Contribution of Active LOs to Perceived Learning.
The active LOs, on the other hand, are stable throughout the 10 weeks of the course. Homework was consistently reported to have the greatest contribution to the learning, quizzes were also said to have had an impact on learning and, according to the students, Blackboard discussions consistently contributed less to their learning of the material. As previously noted, these active LOs also correspond to the required components of the course.
Although the students were given opportunities throughout the quarter to rate the contribution of each LO to their learning, they were asked to do so again on the final survey. The question on the final survey asked them to reflect globally on the contribution of each LO to their overall learning of the course material. The mean overall ratings are in Table 6.
The students reported that the homework assignments contributed the most to their overall learning of the material. This is consistent with responses from the weekly surveys where homework was reported to be the LO having the greatest contribution to learning every week.
No quiz week
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Table 6. Contribution of LOs to Overall Learning
Learning Object
N
Mean
(1=not at all, 5=a lot)
SD
Homework 45 4.71 .66
Quizzes 45 4.31 1.02
PowerPoint slides 45 4.02 1.25
Lectures 45 3.91 1.46
Text 45 3.33 1.38
Blackboard discussions 45 3.02 1.37
To validate the rating data, students were presented with five LOs (quizzes were not included in this ranking question) and asked to rank them based on which they believed had the greatest overall impact on them; the results of those rankings are in Table 7. In this ranking exercise, it was impossible to assign the same rank to more than one item; therefore, students who might have rated, homework and lectures, for example, as both having a lot of impact on their learning were forced to choose which had the most impact, which had the second most impact, and so on. As with the quality and learning contribution ratings previously presented, homework emerged as the most important LO, ranking #1.
Without this impact ranking data, one might conclude that the required LOs would always come out “on top” of the pile in terms of impact on learning; however, note that this is not the case. Homework came out on top for usage and impact on learning, but the 2nd, 3rd, and 4th LOs (lectures, PowerPoint and text) ranked in terms of overall impact were not required LOs and did not rank high in terms of usage (see Figure 4). This is additional evidence of the importance and value of the homework support provided by the CC/MML site.
Table 7. Impact on learning of LOs—Overall Rankings
LO
Rank
Homework 1st
Lectures 2nd
PowerPoint slides 3rd
Text 4th
Blackboard discussions 5th
Quality. In the final survey of the quarter, students were asked to rate the quality of each of the LOs. Table 8 presents the mean ratings (on a 1-to-4 point scale) of each LO. Homework, the LO that students consistently used the most, and that they felt contributed the most to their learning, was rated highest quality; the text, which was used moderately, received the lowest rating.
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Table 8. Overall Quality Ratings of LOs
LO
N
Mean
(1=poor, 4=excellent)
SD
Homework 45 3.58 .54
Quizzes 45 3.22 .67
PowerPoint slides 45 3.11 .91
Lectures 45 3.02 .81
Blackboard discussions 44 2.59 .84
Text 45 2.58 .92
Satisfaction. Two measures were used to determine overall student satisfaction with this online course: a standardized question on the general student course evaluation form distributed to all students at the end of every class and a question on the final online survey of the quarter that asked students whether they would recommend this particular online course. Table 9 shows the frequencies of responses to both items: 58 students completed the course evaluation administered by the University; of those, 86.2% said that the course was outstanding or good. About the same percentage of students who answered the recommend question on the final course survey (86.7%) said that they would recommend the course. Together, these two questions provide compelling evidence to support the claim that students in this online course were overwhelmingly satisfied.
Table 9. Overall Rating and Likelihood to Recommend
Evaluation item Frequency (percent)
Overall course rating
Outstanding Good Fair Poor
26 (44.8%) 24 (41.4%) 5 (8.6%) 3 (5.2%)
Would recommend the course
Yes No
39 (86.7%) 6 (13.3%)
Discussion
Because of the challenges of notation and intricacy of content, mathematics is one of the most challenging disciplines to offer online. However, the availability of rich, publisher-supported online homework sites such as CC/MML and software such as Acustudio has made the creation of LOs for teaching mathematics relatively easy. Acustudio makes possible the creation of rich online lectures that, in the past, would have required extensive instructional technology design support. The ability to show hand-worked examples using the “whiteboard” feature was key to the successful implementation of this software. Students reported that the “examples by hand” created utilizing the whiteboard were an especially useful component of the lectures. However, far and away the most highly utilized and consistently preferred LO was the homework. As shown in the screenshot in Figure 3, the CC/MML site offers a variety of tools for students completing homework assignments. Students are able to view examples, request help solving a problem and link directly to relevant pages in the e-text. In addition,
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students are given immediate feedback on their solutions. This instant feedback speaks also to student preferences as described by Swan (2003). If an incorrect solution is entered, students are able to solve a similar problem (generated by MML) for credit. This rewards persistence and helps students become familiar with procedures and patterns found in solving certain types of problems. CC/MML allows students to interact with the material in a manner that exemplifies the notion of active learning. There is evidence (Bonwell & Eison, 1991; Sahin, 2007) that active participation in content leads to greater and longer lasting understanding of material. Thus, in this online environment, the fact that students engaged with, perceived the values of, and spent a majority of their time doing homework is a positive outcome in terms of student learning online. It would be interesting to compare student performance and preferences to that of a face-to-face class with the same credit structure that offers all the mentioned support mechanisms (including videos) and regular (in terms of time as well as delivery mode) class meetings. This is an area of great interest and may be pursued for verification in future studies. Another area of interest is the lack of value that students placed on the discussion portion of the class. There were, in fact, two aspects of the discussion: a required component and an optional component. The students were only asked to comment on the required component, which consisted of students responding to an instructor “prompt” (a question, problem or statement). The 60 points total for discussion participation were distributed as follows: 3 responses (chosen by the student) were graded for quality (content and communication skills) by the instructor for a total of 30 points (10 points each). The remaining 30 points were given based upon timely and consistent responses to the prompts throughout the quarter. The prompts were designed to encourage students to think more deeply about the material and its applications. Some sample prompts are: “We know that two points determine a unique line. What if you have 3 points? How many distinct lines pass through at least 2 of the given points? Is the answer always the same? How do the various transformations (shifts, stretches and shrinks) affect the equation of a line and the graph of that line (think about the slope and y-intercept)?” and “Find two examples in the newspaper or online of automobile loan offers that require periodic payments and compare the offers.” Thus we see that “discussion” is somewhat of a misnomer for this portion of the course that does not fit the traditional definition of “discussion.” Students were encouraged to respond to each other’s postings but did not often do so. On the other hand, there were optional discussion boards where students could post questions and comments about the course. Because open discussion boards had only optional participation, it was not included in the weekly survey questions. However, in the final survey, “Instructor responses to your discussion postings” was among the course components rated for quality and contribution to overall learning. It is of note that for this final survey, the optional and required discussion boards were not distinguished. In terms of quality, these instructor responses were rated 2nd only to the homework with a mean score of 3.25 (1 = poor, 4 = excellent, SD = .78) while the Blackboard discussions had a rating of 2.59 (SD = .84). In terms of contribution to overall learning, Instructor responses were rated 5th (out of 7) for a mean of 3.64 (with 1 = not at all, 5 = a lot, SD = 1.46) while the Blackboard discussions ranked last overall with a mean score of 3.02 (SD = 1.37).
Features of a face-to-face class that were lost in this online course were useful office hour interactions between student and faculty and partial credit on students’ solutions. While office hours were offered both online and face-to-face, students rarely took advantage of this availability. The online office hours were offered in chat format, limiting the ability to use the required notation for useful interaction, and students generally could not travel to campus to attend face-to-face office hours. It is certainly a difficult mode of communication for mathematics. However, students did interact with the instructor and each other on discussion boards. A potential solution to this problem is offered by a very promising communication software package titled enVision. This software allows for anonymous online communication between students and faculty with rich notational availability. One study (Hooper, et. al., 2006) reports that enVision sessions are more effective than traditional office hours. The software (freeware) allows any number of students to “attend” an online office hour and participate, or lurk, as they choose. Several strengths of the software are described as “Anonymity”, “Engagement and multi-way dialog” and “Passive participation.” Incorporation of enVision into future offerings of the course here are being considered.
Students’ open-ended comments about their online learning experience revealed that there was a great deal of disappointment over the lack of partial credit in the online homework. This will be addressed in future offerings of the course by requiring the final exam to be a traditional “paper and pencil” exam, graded by the instructor. There is also impressive work being done on creating and incorporating partial
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credit in computer-aided homework grading (Ahton, et. al., 2006) and (Livne, et. al., 2007). If these processes were to come to fruition, it would greatly enhance the online homework services currently offered.
Conclusions
The preference, satisfaction, and perceived impact on learning reported by students in this online class are encouraging for students and instructors of online mathematics courses. Students clearly felt that the course was demanding though time consuming. A large majority of the students rated the class as good or outstanding (50 out of 58) and an even greater majority found the class to be intellectually challenging (54 out of 58). This demonstrates that the course, while requiring a lot of work, was perceived as successful by most students. The strong preference for the active learning LO homework coupled with the perceived impact on learning of the lectures lead to the overall impression that the online environment offered these students an extensive, flexible and rich learning experience. While there are some areas of concern, the rate at which tools for instruction online are being developed leads the authors to believe that many will be addressed in due time. The findings in this paper point to a best practices model for online mathematics that strongly utilizes practice problems with fast feedback and integrates tools for content delivery such as media-enhanced lectures. This combination of LOs will provide students with the tools that they need to succeed online.
Acknowledgements
Both authors are grateful for funding from the Faculty Support Grants Program at CSUEB. The first author also thanks the members of the FLC for Best Practices in Online Teaching and Learning and the members of the FLC for the Scholarship of Teaching and Learning. The authors appreciated the reviewers’ comments and have incorporated their suggestions. We feel this has made a stronger paper.
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This chapter provides a national picture of innovativelearning options, such as dual enrollment and early collegehigh schools. These options prepare high school studentsfor college-level course work by providing supported earlyimmersion in college. The chapter also discusses how suchprograms can help a wide range of students and highlightsthe importance of state policy in encouraging these effortsto create stronger connections among high schools, post-secondary institutions, and the workforce.
New Directions for Dual Enrollment:Creating Stronger Pathways from HighSchool Through College
Nancy Hoffman, Joel Vargas, Janet Santos
There are a number of ways to increase high school graduation rates andput more students on the path to and through college. Most states are try-ing to do so by increasing the academic rigor of all their high schools. A firstline of attack is to boost the academic requirements for high school gradu-ation. Fifteen states are instituting a core curriculum that ensures that thedefault pathway through high school is a college preparatory sequence(American Diploma Project, 2007).
Moreover, a substantial number of states are aligning high school grad-uation standards with the standards required to advance directly into non-remedial, college-level work. For example, thirty states are at work on suchalignment through Achieve’s American Diploma Project Network (2007),and other states are engaged in aligning standards themselves. Some statesuse tenth- or eleventh-grade assessments to provide students with informa-tion about their readiness for college. And some states and school districtsare mounting programs to recover high school dropouts and students whofall behind in earning credits: these students too need intensive academicwork to meet the more rigorous standards required to complete high schooland succeed in a community college.
An emerging body of research and practice suggests that providing college-level work in high school is one promising way to better prepare awide range of young people for college success, including those who do
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not envision themselves as college material. Increasing numbers of youngpeople are taking advantage of such opportunities. In some states, such asFlorida and Rhode Island, as many as 17 percent of high school studentsgraduate with college credit (Vargas and Hoffman, 2006; Fletcher, 2006).
If designed well, this college-level work in high school can:
• Increase the pool of historically underserved students who are ready forcollege.
• Provide realistic information to high school students about the knowl-edge and skills they will need to succeed in postsecondary education.
• Improve motivation through high expectations and the promise of freecourses.
• Decrease the cost of postsecondary education by compressing the yearsof financial support needed.
• Create a feedback loop between K–12 and postsecondary systems aroundissues of standards, assessments, curriculum, and transitions from highschool to college.
Across the country, increasing numbers and more varied students aretaking part in accelerated learning options that provide college-level creditduring high school. These options increase the likelihood that students cur-rently underrepresented in higher education will enroll in postsecondaryeducation. Data from the U.S. Department of Education (Adelman, 1999,2006) indicate that the accumulation of twenty college credits by the endof the first calendar year of college is a strong predictor that a student willsuccessfully earn a college credential. If the accelerated high school programis intensive—that is, if students gain twenty or more credits—it is our esti-mation that such credit attainment should also be highly correlated with thestudent’s likelihood of earning a postsecondary credential. In addition, suchcredit attainment is a strong indicator that the student is college ready—thegoal increasingly set by states as the only sufficient outcome of high school.Some accelerated options also have the potential to better link secondaryand postsecondary institutions and to point to better ways to integratefinancing, data systems, and accountability mechanisms across K–16.
Community colleges lead the way in making accelerated learningoptions available. First, their missions include outreach to high schoolsand service to their immediate neighborhoods and regions. Second, inmany of the forty-two states with dual-enrollment policies, public com-munity colleges, not four-year institutions, provide such opportunities.When they are not mandated to do so, community colleges are encour-aged and supported in doing so. Ninety-eight percent of public two-yearinstitutions had high school students taking courses for college credit,compared to 77 percent of public four-year institutions, 40 percent of pri-vate four-year institutions, and 17 percent of private two-year institutions(Kleiner and Lewis, 2005).
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In this chapter, we describe three such options: traditional dual enroll-ment, dual-enrollment pathways, and early college high schools. We thenpresent cases of states and community colleges that have particularly inter-esting models for these options and review the evidence that such optionscan do what they claim: increase college success.
Our organization, Jobs for the Future ( JFF), has worked over the pastfive years with several states and intermediary organizations that are imple-menting early college schools and strengthening their dual-enrollment poli-cies. Based on this experience and national research, we discuss the lessonslearned about practice as well as policy barriers and opportunities posed bythe options. In each section, we highlight the key role played by commu-nity colleges as the leaders in facilitating these options.
One final note is that dual enrollment is also called dual credit, concur-rent enrollment, college in the high school, and joint enrollment. Dual enroll-ment, joint enrollment, or concurrent enrollment typically refer to high schoolstudents taking postsecondary courses, no matter what credit they receive.Dual credit refers to dual-enrollment course taking that results in both highschool and college credit. College in the high school usually refers to collegecourses that are offered on the campus of a high school. Any of these pro-gram variations can fall under the umbrella of what some states call post-secondary, or accelerated, learning options.
Accelerated Learning Options: Definitions andPrevalence
The term accelerated learning options covers a continuum of designs andapproaches. Another common name for these options is credit-based transi-tion programs (Bailey and Karp, 2003). The most intensive of these, earlycollege schools, move students through at least the critical first year of post-secondary education and often through the second year. Dual-enrollmentprograms, although not as intensive, also provide exposure and access tocollege-level work to a large number of high school students.
The most familiar of these accelerated learning options is dual or con-current enrollment. These programs allow high school students to enroll incollege-level course work and earn credit for it while they are still in highschool. Students typically enroll in college courses in their junior and senioryears. In most programs, courses result in dual credit: the college coursereplaces a required high school course, and the student earns credit for both.In some programs, however, students must choose between high school orcollege credit. Most dual-enrollment programs offer free or discountedtuition, providing some savings for families who otherwise might not affordto send their children to college.
In 2006, the National Center for Education Statistics (NCES) publishedthe first national study to attempt to capture the number of students partic-ipating in exam- and course-based college-level learning in high school.
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According to key NCES findings (Kleiner and Lewis, 2005) for the2002–2003 school year, there were an estimated 1.2 million enrollments incourses for dual credit. If a student took multiple courses, schools countedthe student for each course in which he or she was enrolled. Thus, enroll-ments may include duplicated counts of students. Overall, approximately813,000 high school students took college-level courses through postsec-ondary institutions, either within or outside dual-enrollment programs.Using Kleiner and Lewis’s figures (2005), over 15 million students wereenrolled in public and private high schools in the United States in fall 2001(the last year for which data are available). Thus, dual enrollees representabout 5 percent of all high school students. If we assume most course tak-ers are juniors or seniors, the percentage of dual enrollees among these stu-dents rises to approximately 13 percent.
The NCES data are not state specific and therefore do not capturegrowth in dual enrollment in states that have a history of providing suchopportunities and keeping dual enrollment data. In Florida, for example,participation has increased 100 percent between 1995 and 2003 (FloridaBoard of Education, n.d.).
Although participation in community college dual-enrollment pro-grams has existed for several decades, some states and community collegeshave made changes in their purpose, structure, and visibility—previouslythey had existed as an escape from high school for advanced students—andreconceiving them as a path to college and technical education for a widerange of students. In this new configuration, dual enrollment becomes acentral strategy for increasing college-going rates of local high school students. The expectation is that students will receive help in course selec-tion and academic support as needed. In some community colleges, dualenrollees do not have to reapply once they finish their high school require-ments. This sends a strong signal to students that if they succeed in theirfirst course, they can go right on in the host community college.
Dual enrollment has another advantage in making college access moreequitable. In rural and low-income areas where advanced courses may not beavailable to high school students, accelerated learning options may be providedvirtually or by high school teachers or adjuncts certified by a community col-lege. For these reasons, a number of states are making the opportunity to earncollege credit in high school available to every high school student in the state.
A second structure for dual enrollment, and one for which there is notyet settled terminology, is what we call here dual-enrollment pathways.Within a traditional high school, students participate in a preselectedsequence of two to four college courses, sometimes preceded by a “college101” introduction to study skills. The pathway includes opportunities forthose not likely to qualify for college courses before graduation—studentswho are at risk of graduating with weak preparation for college. In addition,such enhanced programs often reach out to middle school students, offer-
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ing them programs that familiarize them with the demands of postsecondaryeducation and the adventure of visiting a college campus.
In dual-enrollment pathways, courses are carefully chosen to meet post-secondary career certificate or general education requirements in two-yearinstitutions and to be transferable. For example, high school students mightbe required to enroll in foundation or gatekeeper courses, such as the firstcollege-level math or English courses, which when successfully completedare highly predictive of earning a credential. The expectation is that studentswill require and receive substantial academic support and that taxpayers willreceive a return on this investment as more young people enter the labormarket with a credential, contribute to the state’s economy, and pay taxes.
In terms of scale, dual-enrollment pathways are not as prevalent as tra-ditional dual enrollment. To qualify as a true dual-enrollment pathway, stu-dents would graduate from high school with anywhere from one to foursemesters worth of college credit. These programs are in very early stages ofdevelopment and thus not yet widely known. Nonetheless, visible modelsexist. With over twenty thousand enrollments in college courses by highschool students in 2004–2005, the City University of New York’s CollegeNow program is the largest and most developed example of which we areaware (Meade and Hofmann, 2007). Middle colleges similarly build path-ways, as do some tech prep programs.
While also relatively small in scale, the third accelerated option, early col-lege high schools, is proliferating quickly and garnering considerable atten-tion nationally. Early college high schools currently serve over fifteen thousandunderrepresented students in integrated pathways and will eventually reachover ninety-five thousand students. Like dual-enrollment pathways, they alignand integrate course sequences across the sectors with the goal of promotingpostsecondary completion. But unlike dual-enrollment pathways, early col-leges are small, autonomous schools. They are designed so that studentsunderrepresented in postsecondary education (low-income students, studentof color, and first-generation college students) can simultaneously earn a highschool diploma and an associate degree or one to two years of credit toward abachelor’s degree tuition free. Each school is developed in partnership with apostsecondary institution whose courses make up the college portion of thestudent’s education. Students begin college-level work as early as ninth grade.
Beginning in 2001, the Bill and Melinda Gates Foundation, in coopera-tion with state and local education departments, philanthropies, and non-profit partners (including JFF, which coordinates the national initiative), havesupported the growth of a national network of over 160 early college highschools in twenty-four states. Sixty-four percent of these schools are part-nered with a community college and are on or near a community collegecampus; another 7 percent have both community college and four-year part-ners ( Jobs for the Future, 2009). In addition, a number of states are creatingadditional early colleges without external funding, largely in partnership with
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their community colleges; several states are using the early college model toreinvent career and technical education.
Early colleges have three designs: grade 6 to 12 schools that incorpo-rate two years of college within the same time as a student would completea high school diploma; four-year programs that incorporate up to thirty col-lege credits by the end of twelfth grade; and five-year programs that start inninth grade and incorporate up to sixty college credits by the end of the fifthyear, which takes place entirely on a community college campus.
Community Colleges and Accelerated LearningOptions: Cases
To demonstrate the variety of ways that community colleges are leaders inenabling the growth of accelerated learning options, we describe how twostates and one system have implemented accelerated learning options. Fordual enrollment, we turn to one of the most extensive statewide programs:Florida’s comprehensive articulated acceleration array of choices for highschool students. For dual-enrollment pathways, we turn to CUNY’s CollegeNow program with an emphasis on its implementation in the six commu-nity colleges among the twenty-three CUNY institutions. For the mostextensive network of early college high schools within a state and oneencompassing both transfer and career preparation, we look at the forty-twocurrently open Learn and Earn schools in North Carolina, thirty-seven ofwhich are partnered with a North Carolina community college.
Traditional Dual Enrollment: Florida. Florida has one of the mosthighly articulated and centralized public education systems in the country.In terms of accelerated learning options, Florida provides multiple meansfor secondary school students to accumulate college credit—AdvancedPlacement (AP), International Baccalaureate (IB), and dual enrollment.However, dual enrollment is perceived as a path to a postsecondary degreeor credential not just for gifted students, but for those considered middleachievers or on a career or technical track. Dual enrollment grew from27,689 students in 1988–1989 to 34,273 in 2002–2003. The growth in par-ticipation for African American and Latino students was especially high dur-ing this period (Florida Board of Education, n.d.).
Florida legislation mandates that all twenty-eight community collegesand specific four-year institutions offer dual-credit courses (Florida Statutes,Chapter 1007.27, 2002). Approximately 80 percent of all dual-credit coursestake place at the community college (P. Cisek to Janet Santos, pers. commu-nication, November 2007). Students may attend courses during the schoolday, before or after school, or during the summer, thereby relieving over-crowding in high schools and maximizing flexibility to participate. Studentscan access Web-based information that provides guidance in choosing col-lege courses. In some community colleges, dual enrollees do not have to
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reapply once they finish their high school requirements, a strong signal tostudents that if they succeed in their first course, they can go directly on inthe host community college.
The state provides incentives for postsecondary degree completionthrough its lottery-funded Bright Futures Scholarship Program (FloridaDepartment of Education, n.d.). The Bright Scholars Program is a merit-basedacademic scholarship awarded to students based on high school transcript andstandardized test scores (SAT or ACT). The program consists of three schol-arship awards: the Academic Top Scholars Award, the Florida Medallion Schol-ars Award, and the Florida Gold Seal Vocational Scholars Award. Participationin dual enrollment receives the same weight as participation in AP and IB forthe purposes of evaluating a candidate’s scholarship application.
Dual enrollment is open to all public, private, and home-schooled stu-dents. The state has established eligibility guidelines recommending that gen-eral education students have a 3.0 grade point average (GPA) and thatstudents pursuing a career certificate have a 2.0 GPA in order to qualify fordual enrollment. Florida also provides dual-enrollment funding for highschool students enrolling in college-level English or math if they have passedthe College Entry Level Placement Test (CPT), the math and English admis-sions exam for the state’s college system (Florida Statutes, Chapter 1011,2002). Additional admission criteria are included in the articulation agree-ment between the community college and the local school district.
Florida’s only restriction on course taking is that courses count simul-taneously for college and high school graduation. The state’s ArticulationCoordinating Committee (ACC), whose members are appointed by andreport to the commissioner of education, is responsible for ensuring asmooth transfer of credit from high school to college. The ACC comprisesrepresentatives from all levels of public and private education: the state university system, the community college system, independent postsec-ondary institutions, public schools, and applied technology education. Italso includes a student member and a member at large. It meets regularly tocoordinate the movement of students from institution to institution andfrom one level of education to the next by evaluating high school courses,including AP, and assigns them equivalency prefixes and numbers thatmatch comparable college courses. Standing committees are charged withsuch issues as postsecondary transitions and course numbering.
Despite the prescriptiveness of Florida’s legislation, the implementationof dual enrollment varies by institution: some provide college in the highschool, and others bring large numbers of high school students onto collegecampuses. Dual-enrollment students are exempted from paying tuition,matriculation, and laboratory fees (Florida Statutes, Chapter 1009, 2002).Each district and its community college partner negotiate how they will sharethe cost of dual enrollment (transportation, faculty salary, advising, and stu-dent support) through their articulation agreement. The state subsidizes the
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purchase of textbooks and other instructional materials only for public highschool students, not for private or home-schooled students.
Florida’s comprehensive K–20 education data warehouse is the nation’sleader in the linking of student-level data across K–12 and postsecondaryinstitutions. The gathering of such information allows the state to generatereports analyzing the effectiveness of its dual-enrollment policy (and its imple-mentation) in helping students meet set educational goals. For example, a2004 descriptive analysis conducted by the Florida Department of Educationfound that high school students who participate in dual enrollment wereenrolling in colleges and universities at rates significantly higher than studentswho did not participate. In addition, Hispanic and African American stu-dents who took dual-enrollment courses were enrolling in higher educationat higher rates than whites or any other ethnic group (Florida Department ofEducation, 2004a, 2004b). The news is encouraging considering previousfindings reporting that only 32 percent of this population of students go onto college within four years of ninth grade (Ewell, Jones, and Kelly, 2003).Such encouraging results led to a much more extensive study published in2007 (Karp and others, 2007).
Dual-Enrollment Pathways: College Now. New York State has nodual-enrollment legislation. But the City University of New York, the largesturban postsecondary system in the country, and the New York Departmentof Education, the largest urban school district in the country, have estab-lished a high school–postsecondary partnership that rivals in size those of entire states. CUNY’s College Now, widely recognized as a national model for an integrated K–16 system, is the country’s most extensive dual-enrollment partnership (College Now, n.d.). Between the 2001–2002 and2006–2007 academic years, enrollment for high school students seeking col-lege credit at City University of New York’s College Now program increasedby 109 percent, from 7,084 to 14,380 students. In 2006–2007, high schoolstudents completed 20,650 credit courses, and 68 percent of total collegecredit enrollments took place at the community colleges (T. Meade to NancyHoffman, pers. communication, January 2005; S. Cochron to Nancy Hoff-man, various communications between October 2004 and March 2005).
The CUNY colleges have long opened their doors to students prior totheir completion of high school diplomas—sometimes to help them completethe diploma or GED program. CUNY’s Collaborative Programs comprise acontinuum of college preparation approaches serving students at differentdevelopmental stages and with different needs: early college high schools, university-affiliated high schools (there are fifteen on or near CUNY cam-puses), and Gear Up serving cohorts in single schools. College Now is anotherexample and offers a range of programs: summer arts and theater activitiesthat acquaint students with college faculty, college culture, and college cam-puses, and, of course, dual enrollment.
College Now’s mission is to help students meet high school graduationand college entrance requirements without remediation and to be retained
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through a degree. Begun in 1984 at Kingsborough Community College, Col-lege Now expanded in 1999 when the CUNY board voted to end remedia-tion at CUNY’s senior colleges. The program was designed specifically toserve students who might not otherwise be able to attend postsecondaryinstitutions and who receive inadequate college preparation in the city’shigh schools. Most CUNY students are poor (average family income is$28,000), and retention and graduation rates are low even at six years fromcollege entry.
The centerpiece of College Now is its free, credit-bearing college courses.College Now differs from most other dual-enrollment options in that coursesare not offered at random but are provided in a structured sequence with aca-demic supports as needed. All credits are transferable within the CUNY sys-tem, but college courses do not necessarily replace high school courses.
In 2006–2007, 29,040 students participated in the program, with 46,888course and activity enrollments. (Activities include noncredit prerequisites tospecific college courses and content-rich workshops, such as an English lan-guage learners history course, to aid in the statewide Regents exam prepara-tion.) College Now models vary, but the largest, at Kingsborough CommunityCollege with 7,699 college credit enrollments in 2006–2007, teaches almostall its courses in high schools. Other College Now programs taught courseson college campuses.
Student eligibility for credit courses is based on Regents exam scores,high school records, and other measures, including substantial personaladvising. While the College Now philosophy is to be stringent about admis-sion to credit courses, the rigor of courses, and the standards of exit assess-ments, the program provides multiple and widespread opportunities forstudents to prepare for these courses. Some College Now programs also helpprepare students for English and mathematics Regents exams and offer non-credit developmental college preparatory courses.
Early College High Schools: North Carolina Learn and Earn. NorthCarolina’s leaders are making dramatic changes to the state’s education sys-tem. A major thrust of these efforts is to prepare more young people forhigh-skills jobs by encouraging them to complete some college before highschool graduation. This is a response to the decline of the state’s long-timeeconomic engines—tobacco, textile, and manufacturing jobs—that used toprovide family-sustaining wages for workers without postsecondary train-ing or education. As the state tries to reinvent its economy and attract inno-vative, knowledge-intensive industries, it must strengthen the educationalattainment of its workforce.
To meet the challenge, the state has invested in early education, raisedhigh school graduation standards, and increased K–12 accountability. It isalso aggressively starting new high schools, creating or redesigning 150schools designed to produce more graduates—and graduates who are on apath to complete college. Early colleges, most of them on community col-leges campuses, are central to this effort.
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Since 2004, North Carolina has opened forty-two early college schools,known in the state as Learn and Earn schools. These currently serve aboutfifty-one hundred students, and the state plans to open thirty-three more(G. Coltrane to Joel Vargas, pers. communication, January 2008). Learn andEarn schools enable students to earn up to two years of college credit or anassociate degree (A.A. or A.A.S. in some cases), along with a high schooldiploma, within five years. Students are reflective of local school districtpopulations, and Learn and Earn targets students not normally found on acollege path.
In 2007–2008, the state invested $15.2 million in Learn and Earn.Starting in 2007, it also made college courses available at no cost to anyNorth Carolina high school student using the Internet through Learn andEarn On-Line. Thirty-seven Learn and Earn schools are partnershipsbetween community colleges and local K–12 districts; four work with four-year institutions (G. Coltrane to Joel Vargas, pers. communication, January2008). Given Learn and Earn’s extensive reach into the public college sys-tem, it represents both a large-scale high school redesign initiative and a sig-nificant investment by the higher education sector in preparing aworld-class workforce ion North Carolina.
North Carolina has long permitted dual enrollment through commu-nity college courses offered exclusively to high school students, and througha concurrent enrollment policy allowing juniors and seniors to take collegecourses with other college students. (These dual-enrollment courses areknown as Huskins classes, named after the North Carolina Huskins bill thatprovided the enabling legislation.) These programs were designed to pro-vide supplemental educational opportunities, particularly for students fromrural communities.
Without altering those programs, the state took steps that allowedLearn and Earn to design dual enrollment as an improved pathway fromgrades 9 to 14. For example, the state created the Innovative Education Ini-tiatives Act in 2003, which authorized state support of cooperative educa-tion programming between high schools and colleges, including foraccelerated programs such as early college and dual enrollment. This laidthe groundwork for state approval of several policy exemptions for Learnand Earn schools. Thus, Learn and Earn schools have avoided policy barri-ers confronted by early colleges in other states that stem from uncoordi-nated secondary and postsecondary education policies. For example, Learnand Earn schools have received a waiver from a state restriction, sometimesfound in other states, on dual-crediting college courses toward nonelectivehigh school course requirements.
North Carolina is also supporting the capacity of its early collegeschools to build and sustain strong partnerships vital to their design. Learnand Earn schools must use some state funds to support a liaison betweenthe high school and college partners. The New Schools Project, funded withprivate and public funds, supports Learn and Earn school implementation
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and sustainability through leadership trainings, instructional coaches, cross-site peer learning, and other services. The project also facilitates data col-lection, advises on research efforts, and reports to policymakers about theprogress of the initiative. Given the size of North Carolina’s effort, Learn andEarn will hold instructive lessons for other accelerated learning optionsnationally.
Research About the Benefits of Accelerated LearningOptions
What is the evidence that accelerated learning options are a means of improv-ing college success? It is promising but still nascent. Many states and programsdo not track or report dual-enrollment outcomes. Fewer have unit-record lon-gitudinal data systems that are capable of telling whether dual enrollees havebetter education outcomes compared to nonparticipants who are otherwisesimilar in social and academic background. However, some studies that uselongitudinal data are available, including recent research on each of the threeaccelerated options discussed here. The research strongly suggests that dualenrollment can prepare high school students for college and give themmomentum in completing a degree or credential. Moreover, it shows thatthese benefits extend to groups who are typically underrepresented in college.
Traditional Dual Enrollment. Researchers from the Community Col-lege Research Center studied Florida’s large statewide program (Karp andothers, 2007). The state’s P-20 data system allowed the researchers to exam-ine the postsecondary outcomes of 36,214 dual-enrollment participantsfrom the high school graduating classes of 2000–2001 and 2001–2002 andcompare them to similar students who did not participate.
Dual enrollees who entered college were more likely to continue for asecond semester and be enrolled two years after high school. At both mile-stones, former dual enrollees had higher GPAs than classmates with no dual-enrollment experience. Dual enrollees also had earned 15.1 more collegecredits on average than nonparticipants three years after high school.Although it stands to reason that some of these credits were earned throughdual enrollment, the researchers deduced that “it is also likely that somewere earned after matriculation into postsecondary education” (Karp andothers, 2007, p. 7).
The Florida data shed light on the benefits of dual enrollment forunderrepresented students because the program serves a wide range of stu-dents. Although participants must meet some academic requirements, theyvary in their academic and social backgrounds. This variation enabledresearchers to look at dual-enrollment outcomes for subgroups such as low-socioeconomic-status (SES) students, African American and Latino stu-dents, and students with lower academic achievement.
In terms of positive effects on first-year and cumulative college GPA,low-income students and those with the lowest high school GPAs benefited
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to a “greater extent than their dual enrollment peers who enter[ed] collegecourses with more social, economic, and educational advantages” (Karp andothers 2007, p. 63). Low-income students also seemed to benefit more interms of greater college credit accumulation.
Dual-Enrollment Pathways. There are similarly positive outcomesfrom CUNY’s College Now. CUNY cooperates closely with the New York CityDepartment of Education, including sharing data across the two systems.Using these data, CUNY’s office of Collaborative Programs Research and Eval-uation has studied the postsecondary outcomes of College Now students whobecame first-time freshmen at a CUNY college during the fall of 2002 or 2003.The research compares participants to nonparticipants who otherwise hadsimilar academic achievements when starting college (Michalowski, 2006).
The evidence suggests that College Now puts students on a pathtoward college completion. Among first-time freshmen, participants weremore likely on average to enroll for a third semester and had higher GPAson average than their classmates with no College Now experience. They alsoearned more credit on average than nonparticipants by the end of their firstyear. First-time freshmen in 2002 and 2003 with College Now experienceearned an average of 1.08 credits more at the end of their first year versusnonparticipants. These figures do not include credits acquired through pre-college dual enrollment or AP programs, which conceivably would haveincreased the number of college credits reported for the participants of Col-lege Now. Most of these positive effects held for College Now studentsacross achievement levels among those admitted to a CUNY campus.
Other findings are notable from the Community College Research Cen-ter’s study, which included both data from Florida and CUNY. In addition topositive effects on retention and GPA, dual enrollment was positively relatedto enrollment in college for Florida students and was positively related toenrollment in a four-year institution for CTE students in CUNY College Now.
Early College High Schools. JFF and the intermediary organizationssupporting early colleges have been collecting data about early college stu-dents, but as the newest of the accelerated options, early college schools stillhave limited longitudinal data. These efforts include JFF’s development ofa Student Information System for the Early College High School Initiativeand the national evaluation of the initiative being conducted by AIR (Amer-ican Institutes for Research) and SRI International. The oldest schools havejust graduated their first classes of students (about nine hundred in all), per-mitting a glimpse at early outcomes.
The data suggest that the schools reach underrepresented student pop-ulations and graduate them with considerable momentum toward a post-secondary degree. Early college schools overall serve students who arerepresentative in race and SES of their local communities. National figuresshow that low-income students comprise at least 60 percent of all early col-lege students, based on free and reduced-price lunch eligibility—a conser-
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vative estimate of the number of students from low-income families sincethey rely on self-reporting by students and their families.
If credit accumulation is indicative of eventual degree attainment, thenearly college schools have put many graduates on a promising path towarda degree. The vast majority (85 percent) accumulated between a semesterand two years of college credit by graduation. The Middle College NationalConsortium, which supports some of the longest-running early colleges inthe nation, reports that its students accumulate an average of thirty-onecredits by twelfth grade and pass their college courses at rates of 92 percentwith an average GPA of 2.78 (Middle College National Consortium, 2008).
Lessons Learned and Looking Ahead: Policy andPractice
Beyond the benefits to the students themselves, accelerated learning optionspoint the way to practices and state policies that can improve the alignmentof the secondary and postsecondary sectors. The options are most likely tobe supported and spread in states with certain policies and by the sametoken exemplify practices for improving college readiness and success thatstates may choose to expand through policy changes.
Policies that are supportive of all accelerated learning options—earlycollege schools, dual-enrollment pathways, and traditional dual enrollment—are guided by the recommendations of a state-level P–16 council, roundtable,or other body representative of secondary and postsecondary education. Anessential starting point for policymaking is agreement on the purpose ofthese programs: ideally, to serve as a bridge to college for underrepresentedstudents as well as a head start on college for those already on their way. Aclearer purpose gives guidance to local partnerships and lends coherence toother policy decisions. Other policies that support local accelerated learningoptions include:
• Encouraging dual crediting and the smooth transfer of college credits toother institutions of higher education
• Ensuring tuition is not an obstacle for dual enrollees• Holding colleges and high schools harmless in financing dual enrollment
so that they can provide joint support of dual enrollees, including throughspecial efforts that recruit and prepare academically underprepared stu-dents for dual enrollment
• Setting eligibility criteria that are agreed on by the secondary and post-secondary sectors and allow students to take college courses in subjectareas for which they have demonstrated readiness based on a variety ofmeasures
• Promoting quality through policies that set minimum instructor qualifi-cations and support teacher training
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• Collecting and reporting data on dual-enrollment participation and out-comes—best done with longitudinal, student-level data across highschool and college
At the level of practice, strong accelerated learning programs requireseveral key elements to create feedback mechanisms and structures for col-laboration across K–12 and higher education:
• Formal structures that link a high school and a partner college such as arenewable partnership agreement; a person serving as liaison betweenhigh school and college; and a decision-making body to design, monitor,and collect data about the program
• A feedback loop to high schools from postsecondary on student success:high school and college transcripts include college course grades and callattention to how well courses are sequenced between high school and col-lege and how well high schools are preparing students for college work
• Shared responsibility (financial and otherwise) by leaders in secondaryand postsecondary education institutions for the continued collaboration
From a narrow perspective, these practices and policies support promis-ing accelerated programs that use dual enrollment. To be more speculative,if research continues to show that these programs have positive effects, theymight be seen as indicative of broad-scale changes needed in practice andpolicy to build a more seamless P–16 education system for all students.
Would not all local high schools and colleges benefit from regular col-laboration to review and improve the efficacy of course sequences in prepar-ing students for postsecondary? How could state finance and accountabilitysystems be more integrated and engender joint responsibility for the suc-cessful transition of all students, especially underrepresented youth, throughhigh school and college?
That said, dual enrollment is no panacea and is not necessarily easy toimplement. Dual-enrollment pathways and early college schools require thathigh schools and colleges work in close partnership, negotiating financingacross the two systems and using dual enrollment as a laboratory for align-ing standards across secondary and postsecondary education. These part-nerships are challenging to build and sustain precisely because the country’ssecondary and postsecondary systems are, by design, disconnected anduncoordinated. Their differing academic calendars, course schedules, cred-iting systems, and organizational norms can make partnership difficult.Accelerated learning programs have the potential to reconcile these divi-sions but are also constrained by them.
These strategies also entail unique costs. Districts, colleges, or statesmust cover tuition and fees for college courses if dual enrollment is to bemade accessible to lower-income students. There are also costs associated
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with maintaining the high school–college partnership such as employing aliaison who coordinates the alignment of curriculum, supports, and profes-sional development across grades 9 to 14.
Another challenge is that college courses offered through dual enroll-ment are only as good as regular courses offered by the college. Becausethere are no common content or learning standards across postsecondaryinstitutions nationally or statewide, course quality takes special effort tomonitor in accelerated programs.
Despite these challenges, accelerated learning options are an importantstrategy for increasing the nation’s high school and college success ratesbecause of their potential for bridging the secondary-postsecondary divide.Given their support of such programs, community colleges are well posi-tioned to remain at the forefront of these efforts.
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NANCY HOFFMAN is vice president of Youth Transitions and director of the EarlyCollege High School Initiative at Jobs for the Future.
JOEL VARGAS is program director at Jobs for the Future.
JANET SANTOS is program manager of district, state, and national policy at Jobsfor the Future.