In an effort to support my intellectual curiosities and union work, I’ve created this dashboard. The vast majority of this information comes from the KU Factsheets and Factbooks.
Continue reading “Quick Dashboard”Efficiency isn’t necessary Efficient in HigherEd
Here’s a follow up to my previous post about student-to-faculty ratios not being related to university finances. I recently asked an administrator if the ratio is a proxy for revenues and expenditures. I was told that the ratio is actually a measure of efficiency.
For my more critical readers, I can hear the groans upon hearing the word “efficiency.” No doubt efficiency is a very corporate term and a stand-in for return on investment. Stepping aside from the very corporate dimensions of that word, efficiency also refers to the relationship between inputs (e.g. resources) to outputs (e.g. a task or function). For example, efficiency can be reducing the amount of energy needed to light up a house. Yet, even from a technical standpoint, efficiency is full of contradictions. Jevon’s Paradox occurs when improvements in energy efficiency lead to more consumption. This increased consumption offsets the potential benefits of “efficiency.” In other words, the technocratic push for efficiency often ignores the real-world deployment of such tools and strategies.
Real-world consequences can be relatively minor like leaving your lights on more since you have energy-efficient bulbs. However, the push for efficiency has had negative consequences in other ways. Edward Tenner (2018) has written about the Efficiency Paradox, noting that efficiency is rooted as much in “racism and xenophobia as in technological idealism” (xii). The reason being efficiency often comes from the top without regard to the social consequences of deploying formulas to optimize whatever those in power want to make efficient. For example, metrics to optimize “safety” can lead to segregation and discrimination in mortgage lending.
What does this mean in education? Is a faculty member teaching more students per class more efficient? Well if efficient means cheaper, then yes. However, what sort of consequences come with that? Retention and graduation rates come to mind. This is especially going to be costly for first-generation, those with disabilities, LGBTQ, non-traditional, and students of color. They need a diverse faculty who can provide mentorship and a safe space for them throughout their careers. As such, an efficiency metric solely based on increasing class sizes might not solve the financial problems caused by decreased enrollment. Then, of course, we are now in the world of COVID-19. Larger classes can limit options for physical distancing.
I conclude with this final thought on metrics. Our system has other metrics for financial sustainability they are not using. For instance, they have “Education and General (E&G) Expenditures per Student FTE.” This is a bit better since we are back to talking about actual finances. However, there’s a political component. When they propose they are increasing the student-to-faculty ratio, they are saying they want to spend less per student. This E&G metric would confirm that. The optics here are very different than suggesting a ratio of 20:1. I believe that this is why they chose this problematic student-to-faculty metric, versus more accurate ones for examining financial sustainability.
Criticizing Student-to-Faculty Ratios
There are a lot of metrics or methods of measuring what we do in higher education. An important one for us professors is faculty full-time equivalent (FTE), which is a percentage calculation of a single faculty member’s teaching. In other words, an FTE of 1.0 represents a full-time professor. Two people hired half-time would also be 1.0. At my institution and system, it is primarily based on teaching load. In my case, teaching my full 4/4 load is represented as 1.0 in a spreadsheet. In that spreadsheet, there is also a tally of all faculty to get an overall number of faculty FTE, which is 428.61 for Fall 2019. This is also done for students and staff as well as using other formulas for measuring the notion of full-time.
Continue reading “Criticizing Student-to-Faculty Ratios”Faculty Diversity & Hiring
In a previous post, I had indicated that more diverse departments (social sciences, math, and business) generally have an above average number of students per term. In this post, I want to discuss issues in diversifying faculty. Why? My faculty union recently tweeted this image
While the expression of solidarity with fellow academics is important, the optics of the image is just plain bad. The lack of racial and ethnic diversity in the photo is real problem. One long-time union leader indicated to me that this is a long-standing problem with our organization.
In this post, I would like to look at how lack of diversity happens – at least on my campus. While administration gives departments lines, it is ultimately up to departments to put in the effort (if that’s what they really want to do) and hire more faculty of color. At the same time, faculty searches are complicated. It is hard to say exactly why a single search turned out the way that it did. However, we can see patterns across multiple searches. So here is my analysis of faculty hiring and diversity in my College of Liberal Arts and Sciences using available data.
Using the College’s annual newsletter, I looked at new tenure track hires (or temporary conversions) between 2012 and 2018. In this 7-year period of time 12 out of 15 departments gained tenured track faculty. I’m using the term “gained tenured track” rather than hire, because – I estimate – a large number of these professors were temporary/adjunct faculty at one point. I have also chosen to obscure the names of the departments to reduce blowback. However, I suspect it is pretty easy to decipher which department is which if one really wants to find out.
Table 1: New Tenure Track Faculty 2012-2019
|
Dept
|
# TT
|
|
A
|
9
|
|
B
|
4
|
|
C
|
3
|
|
D
|
2
|
|
E
|
4
|
|
F
|
3
|
|
G
|
4
|
|
H
|
4
|
|
I
|
2
|
|
J
|
2
|
|
K
|
1
|
|
L
|
1
|
In addition, I looked at data from our Office of Institutional Research, and found that all staffing (including secretaries, faculty and administration) in the CLAS is 79.8% white. Then looked at the demographics of the 12 departments that gained a tenure track faculty member. Below in Figures 2a, b, c you can see the number of faculty/staff of color, overall department size, and percentage faculty/staff of color (or those who didn’t identify as white).
Table 2a: 2012 & 2019 Department Demographics
|
Department
|
A
|
B
|
C
|
D
|
||||||||
|
|
# Faculty of Color
|
Dept
|
% Faculty of Color
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
|
FALL
|
1
|
35
|
2.9%
|
7
|
22
|
31.8%
|
6
|
14
|
42.9%
|
2
|
13
|
15.4%
|
|
FALL
|
4
|
42
|
9.5%
|
8
|
27
|
29.6%
|
4
|
12
|
33.3%
|
2
|
13
|
15.4%
|
Table 2b: 2012 & 2019 Department Demographics
|
Department
|
E
|
F
|
G
|
H
|
||||||||
|
|
# Faculty of Color
|
Dept
|
% Faculty of Color
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
|
FALL
|
6
|
21
|
28.6%
|
1
|
8
|
12.5%
|
5
|
14
|
35.7%
|
2
|
19
|
10.5%
|
|
FALL
|
4
|
14
|
28.6%
|
0
|
9
|
0.0%
|
3
|
11
|
27.3%
|
3
|
21
|
14.3%
|
Table 2c: 2012 & 2019 Department Demographics
|
Department
|
I
|
J
|
K
|
L
|
||||||||
|
|
# Faculty of Color
|
Dept
|
% Faculty of Color
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
|
FALL
|
3
|
25
|
12.0%
|
3
|
17
|
17.6%
|
6
|
15
|
40.0%
|
1
|
13
|
7.7%
|
|
FALL
|
3
|
26
|
11.5%
|
3
|
21
|
14.3%
|
7
|
20
|
35.0%
|
1
|
16
|
6.3%
|
From Table 1 it is clear that hiring is incredibly uneven. Department A gained 9 tenure track faculty in a 7-year period of time. 9 out of 39 new tenure track faculty in this period of time, or 23% of new faculty in the college joined Department A. In terms of diversifying the university, it can be argued that this department was given more opportunities to recruit faculty than any other department in our college. Yet, this department – which was not particularly diverse – actually became less diverse over time as seen in Table 2a.
At the same time, we also see departments that do not receive many (or any) lines are not likely to become diverse. For instance, Department L only had 1 hire/conversation. While this department is pretty homogenous, they have had far fewer opportunities to diversify. This may be obvious, but it is clear some departments have greater power to change than others.
While other departments received fewer new tenure track faculty, there are some interesting observations to be made. For instance, we can look at Department F, that had zero faculty of color and managed to recruit someone of color in one of their 3 searches/conversions.
Put another way, decisions made by Department A have wide ranging implications for faculty demographics. Blame might not be the right word, but they perhaps have a greater responsibility to think about the bigger picture. Departments that get lines, especially those that get repeat opportunities can dramatically change the campus climate for faculty of color. To put this into perspective, about 21.7% of our 479 faculty aren’t white. There were only 16 Black, 24 Latinx, and 48 Asian faculty members in Fall 2018. Given how low these numbers are, every new hire of a scholar of color is significant.
How do we explain Department A?
I do think it is worth noting that, according to the 2017 Survey of Earned Doctorates, US citizens and permanent residents in his area of study are 79.3% white. This is also a field in which people do study communities of color and their culture. So, I have no doubt there are those who recognize the problem. This issue is likely due to 1) specific area of search and existing faculty interests 2) our geographic location 3) the way in which people are biased toward those that look the same, or come from similar backgrounds. The question, however, is whether people who realize there is a problem are willing to challenge the status quo, and be more creative in running searches. This also requires administration to help departments try new models of hiring. This is something other institutions have effectively done.
Consequences
There are a lot of consequences, but I want to focus primarily on university service such as involvement in the union. While large departments have downsides, a plus side is that workload can be spread out over more faculty. This includes department-level work, but also university-wide service. Politically, this can have consequences. Representation in our local union’s representative assembly is based on department size. In addition, large departments have an easier time having gaining additional representation through elected leaders in various “shared governance” bodies.
For existing faculty of color, this means more work. It is well documented that faculty of color do a lot of “invisible labor” through their service activities. Again, with so few black and Latinx faculty, individuals are repeatedly being ask to do more and more work.
In conclusion, I suspect if I were to look at data for other large departments in other colleges at my university, I may see something similar. Again, I would like to emphasize that large departments that receive lines have greater responsibility to the campus community to critically examine their search procedures.
Some data on promotion at my university
In this blog post, I would like to provide some data for my colleagues on promotion at our university. I have heard many different comments in regards to research and publications. However, there appears to be very little data, or evidence beyond anecdotes describing what’s going on systematically. So, I’ve sat down and put this estimate together. The following chart of search “results” for publications was created using our Daily Brief newsletter announcements, and doing searches on Google Scholar.
| Assistant-Associate Professor | Associate-Full Professor | |||||
| Year | # Promoted to Associate | MEAN Results
(Prior 5 Years) |
Median | # Promoted to Full | MEAN Results
(All Years Prior) |
Median |
| 2010 | 11 | 2.45 | 1.00 | 7 | 6.28 | 7.00 |
| 2011 | 16 | 3.00 | 2.00 | 5 | 6.66 | 7.00 |
| 2012 | 14 | 2.00 | 1.00 | 1 | 2.00 | 2.00 |
| 2013 | 19 | 2.00 | 1.00 | 5 | 4.50 | 3.50 |
| 2014 | 19 | 4.00 | 2.00 | 5 | 12.40 | 13.00 |
| 2015 | 19 | 2.00 | 1.00 | 10 | 3.64 | 1.50 |
| 2016 | 14 | 2.43 | 1.00 | 13 | 5.90 | 4.00 |
| 2017 | 13 | 2.23 | 1.00 | 16 | 12.37 | 6.00 |
| 2018 | 13 | 2.69 | 3.00 | 6 | 10.83 | 12.00 |
| All | 2.40 | 1.00 | 7.86 | 6.00 | ||
These numbers should be considered estimates, for the following reasons:
- Promotion is not only linked to “Scholarly Growth” per our union contract. It includes teaching and service. The numbers to not necessarily suggest a “minimum” needed for promotion.
- The above only includes those listed in the Daily Brief, and does not include those who were later promoted through a union grievance, or lawsuit.
- Google Scholar under-indexes the humanities, and of-course those in the arts might be in fields where one doesn’t publish to gain tenure or promotion. Also, as publishers put more past material online, sometimes these numbers change.
- Google Scholar results used are simple counts. There is no differentiation between books or articles. However, our union contract explicitly states that the evaluation process should use quality over quantity.
- At the same time, it should be noted that Google Scholar counts also include book reviews, non-peer reviewed reports, as well as publications in predatory journals. However, it should be noted that there was not a concern regarding predatory publications by our university administration until 2016.
- It is important to note that our system separates tenure and promotion to associate professors. This means it is possible to receive tenure and be denied promotion to associate professor. It also means someone can choose not to apply for promotion. Nonetheless, for convenience, I have used results in the 5 years leading up to promotion, which is time time-frame when most faculty will also be applying for tenure. However, in several cases people took longer than 5 years to be promoted to associate.
- For data on full professors, I’ve chosen to use lifetime results prior to the year in which the individual was promoted. The range in which people on our campus become full professors range from 3 years, to decades, after they receive promotion to associate. Without direct access to everyone’s CVs, it’s really hard to come up with a perfect way to delimit time-to-full.
In the absence of looking at actual publications (not just results) and creating a more nuanced coding system, I did look at disciplinary fields, and academic unit/college. For instance, our College of Liberal Arts & Sciences (CLAS) is where most of the traditional “research” fields within the humanities, social sciences, and STEM are located. Looking at that breakdown, we see for promotion to Associate Professor for those in Humanities fields, there was a mean of 2.06 results. For the Social Sciences there was an average of 3 results, and for STEM fields an average 3.97. For promotion to Full Professor in CLAS, we see means of 4.85 for Humanities, 11.63 for Social Sciences, and 10.57 for STEM.
Finally, below is data from our Office of Institutional Research regarding faculty ranks.
Working Over The Summer
APSCUF (my faculty union) currently has a blog series that examines what professors do when class is not in session. This is a response to politicians characterizing our workload as being only 17 hours a week. Pennsylvania professors are not alone in sharing their “off contract” and summer activities. Faculty in Connecticut are keeping busy. So important are the summer months to our professional work, faculty at the University of Massachusetts at Amherst have written an advice piece for Inside Higher Ed on how to get the most out of the summer (and not burn out). I have my own blog post on summer writing written two years ago. For this post, I’d like to add to the discussion of – not just how much we work as faculty – but how important our so-called “off” time is.
Indeed, for me, as well as my colleagues, there is no “time off.” We work year round, but time for different activities may be allocated differently throughout the year. Summer is when I do much of my course preparation for the next academic year. This means reading new books on the areas I teach, revising syllabi, and updating data in my PowerPoints. This probably is not surprising to those outside of academia.
Summer is absolutely necessary for research and writing, which is not included the politicians’ 17 hour calculation. While we are not paid for the summer (unless we teach), this is when many of us conduct the research that is integral to our jobs as teachers and educators. At teaching oriented institutions, such as the PASSHE system, summer “free time” is even more important for continuing our scholarly growth. During the regular academic year, the time needed to manage four courses per term, grading, student advising, as well as committee and service work makes it extremely difficult to focus on research and writing.
For example, I study cities and globalization. Summer is my chance to travel to the places I study. In the past, I have visited universities in Ethiopia and Turkey. Last summer, I participated in a conference in Italy. While overseas, I am not only interacting with other scholars, but also investigating the processes that shape urban life. The only way this can be done without interfering with my teaching is to do it during the summer. This work is not just “research,” but it helps me in the classroom back in Pennsylvania. By conducting research, I am also preparing for my teaching. In gaining first hand knowledge and other experiences to share with my students, I can be a stronger teacher.
Summer is also the time in which I write up my research. In my field, this means an 8,000 to 10,000 word article that goes through many rounds of revision before submission to a scholarly journal for review by peers and other experts in the field. I believe that my strength as a teacher comes from my ongoing research and writing. Rob Jenkins, who writes for the Chronicle of Higher Education, has discussed how writing helps him in the classroom. Personally, I push myself to write for the same reasons we make our students write. It forces me to actively engage the literature and current trends in the field. This requires reading what others of written, thinking about my own research, and figuring out a way to make an effective argument. Furthermore, I submit myself to peer review for the same reasons why peer review is good for student writing as well. It forces me to clarify and effectively communicate ideas – valuable skills in the classroom.
As a sociologist, the American Sociological Association (ASA)’s annual meeting in August typically marks the end of summer. In the past four years, Kutztown has sent six undergraduate students to the ASA Honors program. This puts us in the company of elite research schools and selective liberal arts campuses – campuses that provide greater institutional support for research and professional development. Supporting student research and encouraging students to apply for such programs, requires active engagement in the discipline. My colleagues and I do this, because it is part of our professional identities – which extends beyond our specific university employment. This is tied to our passion for our field, research and desire to share the discipline with our students. In order to do this, we need to keep up with our research and spend our summers preparing for our annual conference.
In conclusion, our “off contract” time is valuable to both our professional identities, as well as our students. We go above and beyond because of we made the decision to devote our lives to the study and teaching of our disciplines. Claims by politicians that we only work 17 hours and have summers off demonstrates both a lack of understanding and respect for our profession.
Criticizing Return-on-Investment Approach to Degrees in PA
A version of this post appears in the APSCUF-KU May 2016 Newsletter.
Earlier this year, Pennsylvania’s System of Higher Education (PASSHE) issued a press release on a report entitled Degrees of Value. This report from Georgetown University’s Center on Education and the Workforce will become part of the State System’s “Program Alignment Toolkit.” Looking at undergraduate degrees and income, the report essentially takes a return-on-investment (ROI) approach to college degrees. In PASSHE’s press release, it noted that: “While college-educated employees in any field tend to earn more than those with only a high school education, the college majors that lead to the highest earnings are in STEM, health and business. For example, a major in architecture and engineering, the highest-paying area of STEM, led to average earnings of $82,500 in Pennsylvania.”
The ROI approach to undergraduate programs is highly problematic and often criticized. Not only are there problems with its logic, it is typically used as an attack on the arts and humanities. APSCUF, the union representing faculty in the PASSHE system, has issued its statement on the report. However, I would like to offer my thoughts on the report. I do not find the results of the report particularly surprising. What is disconcerting is that the document lacks nuance even when using a ROI rationale and the report’s own data.
Take for example the state average for students who majored in the humanities and liberal arts. Median earnings for a humanities and liberal arts major between the ages of 12-64 is $45,300 statewide. However, a humanities and liberal arts major in the Southeast region of the state makes $49,900, which is more than a biology and life science major living in the Northwest region of the state ($46,400) and pretty close to a biology major in the Southwest region ($51,000).
|
|
Biology & Life Science | Humanities & Liberal Arts |
| Central Region |
$58,500 |
$44,100 |
| Northeast Region |
56,800 |
40,000 |
| Northwest Region |
46,400 |
36,100 |
| Southeast Region |
67,300 |
49,900 |
|
Southwest Region |
51,000 |
41,200 |
|
Statewide |
59,700 |
45,300 |
| Source: Degrees of Value, Figure 14, pages 23-24 | ||
The Degrees of Value report only briefly discusses geographic differences. However, it only does so within majors. This is because using income as a benchmark is complicated by significant regional differences in jobs, cost of living, and economic resources. Yet, the report’s focus is solely on income.
PASSHE’s acceptance of the report reinforces faculty fears of a vocational-drive by campus administrators and state leaders. Yet, the data within the report does not support a vocational-drive based on ROI. Students majoring in the social sciences make more than those in fields such as agriculture and natural resources, education, law & public policy, journalism, industrial arts, and social work.
| Major | Median earnings by undergraduate major group ages 21-64 |
| Social Sciences | $52,800 |
| Agriculture & natural resources | 50,800 |
| Education | 47,800 |
| Law & public policy | 46,700 |
| Communications & journalism | 43,400 |
| Industrial arts, consumer services & recreation | 42,100 |
| Psychology & social work | 42,100 |
| Source: Degrees of Value, Figure 12, page 20 | |
In addition to the report’s focus on STEM-H, business majors are a focus. Yet, social science majors in the Southeast Region do better than many business majors across the state.
|
Business |
Social Sciences (excluding psychology and social work) |
|
| Central Region |
$55,900 |
$49,500 |
| Northeast Region |
50,500 |
42,100 |
| Northwest Region |
46,300 |
42,900 |
| Southeast Region |
67,300 |
60,500 |
| Southwest Region |
55,000 |
47,100 |
| Statewide |
58,900 |
52,800 |
| Source: Degrees of Value, Figure 14, pages 23-24 | ||
It is also important to note that nationally, the gap between humanities & social science, and professional & pre-professional fields closes significantly over the course of a worker’s career.
Source: Chronicle of Higher Education, AAUP.
In conclusion, the equating of undergraduate degree with income is simplistic. It ignores economic geography, labor market dimensions, as well less quantifiable benefits such as career satisfaction, community service, and job security.