Queens College Online Course Evaluation Pilot

Transcription

1 Queens College Online Course Evaluation Pilot Report of Results: April 2, 2009 Teaching Excellence and Evaluation Committee -Susan Croll, Chair -Chantal Bruno, student -Claudia Perry -Jill Frohmann, student -Kimberley Alkins -Alison Ratner, student -Kate Pechenkina Ex Officio: Steve Schwarz, Meg McAuliffe Guests/Contributors: Dean Savage, Eva Fernandez

2 Reasons for move to online evaluations Financial: online evaluations would be substantially less expensive an important consideration during this economic crisis Environmental: online evaluations are more in-line with Queens College s Green initiatives than paper and pencil surveys Access: 30% of all courses never distribute their evaluation forms therefore, not all students get equal access to evaluation opportunities

3 Issues of concern Response rates are generally lower with online evaluations we hoped for 30-35% rate No assurance that the distribution and spread of scores would be similar for online evaluations No assurance that the mean scores would be similar for online evaluations

4 Fall 2008 Pilot All sections were evaluated, as was intended for Fall 2008 Same 22-question format employed as for paper and pencil evaluations Evaluation period spanned the 3 weeks up to and including the official last day of classes

5 Solicitation of Student Responses Initial sent to all students with link to their evaluation page via LotusNotes and alternate address provided by students reminder sent Posters placed around campus refreshed twice Announcements appeared on the QC home page and on the plasma boards s were sent to Chairs and faculty asking faculty to urge students to participate

6 Incentives 83 prizes were available via lottery for all students who submitted evaluations (i-pods, parking passes, bookstore & food gift certificates) Student Association publicity encouraged a culture of responsibility RULED OUT: receipt of grades contingent on submission of evaluation (results in close to 100% response rate, eg. UCLA Medical School; Murphy, 2004) RULED OUT: course-related incentives (eg. UC-Irvine; Murphy, 2004)

7 Online Evaluation Pilot Results Queens College, Fall 2008

8 Response Rates Percent of sections evaluated with paper and pencil, average for past semesters 70%; Sections evaluated online Fall 2008, 93% Total responses received with paper and pencil, average for past semesters ranged from 49-54%; Evaluations submitted online Fall 2008, 29% (19,681 responses)

9 Response rates varied by department, some met paper response rates Department/ Program Honors Environmental Science Physics Biology Library & Information Science Biochem ECP-Counselor Education Chemistry # responses #enrolled % responses

10 Department # responses # enrolled % responses Student Personnel Japanese Computer Science Honors in Math & Nat Sciences Linguistics & Communications Disorders Portuguese Media Studies Arabic Middle Eastern Studies Business & Liberal Arts Anthropology ECP-School Psychology Labor Studies Sociology Psychology Art (Studio Art) Astronomy Spanish English Others above the average of 29%

11 Anecdotal Questioning of High- Response Departments Faculty strongly encouraged by Chair or other Champion to advertise the evaluations in class Students told WHY it was important to participate in the evaluations (why it helps them, why it helps faculty) UCSF increased response rates via student education (Murphy, 2004)

12 Developing a culture of online evaluation takes time Course Evaluation Response Rates for Drexel University Online Course Implementation Semester Response Rate Fall % Fall % Fall % data taken from McGourty, Scholes, and Thorpe, 2002

13 Mean Scores Fall 2008 Pilot

14 Question S 01 F 02 S 04 F 05 S 07 F 08 Q1 Requirements clear Q2 Presentations clear Q3 Good English Q4 Enthusiastic Q5 Exams clear Q6 Comments useful Q7 Work returned in reasonable time MEAN SCORES Q8 Reading valuable Q9 Other assignments valuable Q10 Respectful of students Q11 Concerned about progress Q12 Available outside class Q13 Encourages questions Q14 Learned a great deal Q15 Enjoyed course Q16 Difficulty of course

15 Question S 01 F 02 S 04 F 05 S 07 F 08 Q1 Requirements clear Q2 Presentations clear Q3 Good English Q4 Enthusiastic Q5 Exams clear Q6 Comments useful Q7 Work returned in reasonable time MEAN SCORES Q8 Reading valuable Q9 Other assignments valuable Q10 Respectful of students Q11 Concerned about progress Q12 Available outside class Q13 Encourages questions Q14 Learned a great deal Q15 Enjoyed course Q16 Difficulty of course

16 Question S 01 F 02 S 04 F 05 S 07 F 08 Q1 Requirements clear Q2 Presentations clear Q3 Good English Q4 Enthusiastic Q5 Exams clear Q6 Comments useful Q7 Work returned in reasonable time MEAN SCORES Q8 Reading valuable Q9 Other assignments valuable Q10 Respectful of students Q11 Concerned about progress Q12 Available outside class Q13 Encourages questions Q14 Learned a great deal Q15 Enjoyed course Q16 Difficulty of course

17 Means & Standard Deviations Question Number

18 Narrowing down reasons Could the decrease in scores be due to the inclusion of the 30% of courses never evaluated before (i.e. could those be the courses students dislike most?) To investigate: Conduct an analysis of all courses taught by the same instructor in last two full evaluation periods: SPRING 2007 versus FALL 2008

19 Spring 2007 vs. Fall 2008 Repeat Course/Instructor Combinations

20 Spring 2007 vs. Fall 2008 Repeat Course/Instructor Combinations CONTROL FOR NON-SELECTIVE RESPONSE BIAS

21 Spring 2007 vs. Fall 2008 Repeat Course/Instructor Combinations NOT ALL MEASURES IMPACTED

22 Spring 2007 vs. Fall 2008 Repeat Course/Instructor Combinations STUDENT GRADES SIMILAR

23 Spring 2007 vs. Fall 2008 Repeat Course/Instructor Combinations MORE LOWER CLASSMEN

24 Narrowing down reasons Could the significant difference in scores be due to the difference in class level of student responders? We had fewer upperclassmen with online evaluations. To investigate: ANCOVA run to covary out grade level

25 Results of ANCOVA Class level significantly impacted all measures of course/instructor evaluation except for timely return of work, reading valuable, and other assignments valuable (work-related measures) However, covarying out class level did not eliminate significant effects it only reduced the size of the effects slightly

26 Summary of Mean Score Changes For most course-instructor evaluation measures, mean scores decreased with online evaluations While significant, this effect was small (effect size=.063). The average decrease was.19, and this decrease was very consistent across sections and measures. Notification of this adjustment for Fall 2008 will be provided to Department Chairs, P&B Committees, and Administration

27 Unlikely reasons for decline in scores Fall versus Spring semester Inclusion of 30% previously excluded courses Differences in student class year, GPA, or expected grade in course

28 Some potential remaining reasons for decline in scores Students were more motivated to participate when they disliked course student responders skewed toward these students Fall 2008 was an unusual semester Online course evaluation represents a more honest evaluation of courses and instructors, and the lower values are more accurate

29 Some potential remaining reasons for decline in scores Students more motivated to participate when they dislike course student responders skewed toward these students Solve this problem by increasing response rates if we stay with an online format, we need to work toward this goal Fall 2008 was an unusual semester Cannot determine whether Fall 2008 was unusual independent of online evaluations without repeating the online evaluations Online course evaluation represents a more honest evaluation of courses and instructors, and will always be lower Cannot determine whether this is true of Queens College students without collecting additional data, though some data in the literature suggests this possibility

30 Brooklyn College Study HONESTY OF RESPONSES -58% of students reported believing that students are more honest on online evaluations (specifically, RMP) -38% believed online and paper equally honest -8% believed paper more honest VALIDITY OF RATINGS -47% of students reported believing that online evaluation results are more representative -34% believed online and paper equally representative -17% believed paper more representative Brown, Baillie, and Fraser, 2009

31 Could scores be truly lower online, independent of response rate? Few studies have addressed this One study out of Idaho State (Heath, Lawyer, Rasmussen, 2007) randomly assigned students to online vs. paper from same classes, and then totaled subscales to compare overall scores for online versus paper No confounds from course, semester, season, etc.

32 Total Evaluation Scores for Idaho State (response rates 72.2% online) vs. Queens College (response rate 29% online) (p=.098, n=130) (p=.001, n=642)

33 Bottom line Our mean course ratings are lower, albeit only 0.2 lower on average. Without additional data, we cannot say for sure why. Our response rates were 29% on our first time out we d like to work to improve that.

34 *reported successful across multiple campuses, eg. Columbia University, Hmieleski (2000) Improving response rates Continue incentive lottery Continue advertising on web, plasma boards, and posters The library has offered two computer labs for faculty to reserve in order to allow students to conduct evaluations during class time Department Chairs will be asked to forward this information, especially to untenured, tenuretrack faculty *Implement more frequent reminders success reported with reminders every 3 days *More aggressively urge faculty to advertise evaluations in their courses, and to explain why it s important for students to complete them

35 TEEC voted to continue online evaluations for one year (resolution to follow). Rationale: Administration greatly supports moving to an electronic format due to cost, Green initiatives, and a movement nationwide toward technologybased evaluation We want to foster a culture of continuity and expectation for the online evaluation system in order to help drive up response rates We need more data in order to determine if lower scores were 1) a fluke, 2) caused by low response rate, or 3) a permanent fixture for online evaluations

36 Aren t we worried about the lower scores? Of course. However: The errors were tight for the decreases, showing a global, across-the-board drop of about 0.2 points per measure this makes the hit uniform and predictable We will provide reports and data to all Chairs, P&B s, and to administration so that expectations can be adjusted for Fall 2008 and any subsequently impacted semester

37 Resolutions: 1) We, the Queens College Academic Senate, resolve to extend online course evaluations to include the Spring and Fall semesters of ) We, the Queens College Academic Senate, resolve to conduct evaluations of all courses each semester that online evaluations are in effect.