Assessment Details
Academic Year: 2021-2022 Level: Graduate
Campus Department: Morrissey College of Arts & Sciences [UG and Grad]
Program Type: Major [UG] / Program [Grad]
Program Name: Psychology and Neuroscience PhD (Link)
Description of Data Collection:
At each student’s Ph.D. dissertation defense, the committee members and the student fill out a questionnaire to assess the degree to which each learning objective has been achieved (on a rating scale from 1 to 7).
Placement and publication data for graduate students are recorded annually.
Review Process:
The Graduate Program Committee meets each year to analyze all of the questionnaires from the previous year (described in the previous section) by aggregating the responses for each question to evaluate how well our graduate program is meeting each of the learning outcome goals described above. At a faculty meeting, the Graduate Program Committee proposes changes to the graduate program in an effort to better meet each of the learning outcome goals. Each proposal is discussed and voted on by the faculty, and if approved, the corresponding change to the graduate program is implemented.
Resulting Program Changes:
The ratings from the Ph.D. students that graduated within the last year were considered when evaluating the program.
For committee members, the average assessment ratings on the learning outcomes described in section 1, on a 7-point scale, were: 6.9, 6.9, 6.9, 7.0, 6.7, and 6.9.
For graduate students, the average assessment ratings on the learning outcomes were: 7.0, 7.0, 6.4, 6.8, 6.8, and 6.8.
The ratings were all very good (ranging from 6.4-7.0); however, the third outcome corresponding to “Understanding statistical theory and application in their area” had a more modest rating from graduate students. Based on this, and past more modest ratings for this outcome, the 1-credit Programming Lab, which is linked to the required graduate statistics course, will be taught as a required 2-credit course starting this Fall. Moreover, rather than being taught by an advanced graduate student, the Programming Lab will be taught be a faculty member. Finally, in 2020, Brooke Magnus, Assistant Professor in our department, began teaching the course Statistics & Experimental Design, which is required for all first-year graduate students and one of the most difficult courses in the curriculum. Professor Magnus has excellent teaching ratings for this course; her ability to teach statistics very well is expected to also increase the ratings for this outcome in the future.
Date of Most Recent Program Review:
The ratings from the Ph.D. students that graduated within the last year were considered when evaluating the program.
For committee members, the average assessment ratings on the learning outcomes described in section 1, on a 7-point scale, were: 6.9, 6.9, 6.9, 7.0, 6.7, and 6.9.
For graduate students, the average assessment ratings on the learning outcomes were: 7.0, 7.0, 6.4, 6.8, 6.8, and 6.8.
The ratings were all very good (ranging from 6.4-7.0); however, the third outcome corresponding to “Understanding statistical theory and application in their area” had a more modest rating from graduate students. Based on this, and past more modest ratings for this outcome, the 1-credit Programming Lab, which is linked to the required graduate statistics course, will be taught as a required 2-credit course starting this Fall. Moreover, rather than being taught by an advanced graduate student, the Programming Lab will be taught be a faculty member. Finally, in 2020, Brooke Magnus, Assistant Professor in our department, began teaching the course Statistics & Experimental Design, which is required for all first-year graduate students and one of the most difficult courses in the curriculum. Professor Magnus has excellent teaching ratings for this course; her ability to teach statistics very well is expected to also increase the ratings for this outcome in the future.
Attachments (if available)