Category: Blog

Rethinking the President’s Role in Fundraising

by Jim M. Langley

Because your institution’s president is uniquely positioned to scan the horizon and help develop and communicate a vision of the future to prospective donors, his or her role in fundraising entails far more than just making connections and making the ask. In his recent monograph “Fundraising for Presidents: A Guide,” Jim Langley, president and founder of Langley Innovations and past vice president for advancement at Georgetown University, contends that the president’s primary role in fundraising is not to ask for money but to create the conditions that attract significant philanthropic investments. We followed up with Jim Langley this week to learn more. FUNDRAISING FOR PRESIDENTS: A GUIDE Jim Langley’s monograph offers a forward-thinking look at: Slow Persistence, Not Rapid Persuasion We asked Langley for the key thing presidents need to know about philanthropy. In response, Langley noted a fact that is relatively well-known but infrequently (or inconsistently) acted upon. “Fundraising,” he cautions, “is often depicted as a short-term if not transactional phenomenon, while the research on philanthropic patterns suggests that fundraising needs to be long-term in its focus.” Citing research on donor trends and behaviors, Langley notes that: Langley uses this data to issue a reminder to institutional leaders that […]

Twitter and Learning

What are specific ways that faculty can use Twitter in the classroom – and outside it – in ways that aid student learning? Several studies at Michigan State University over the past couple of years have produced some fascinating findings about college students and Twitter: A 2010 study led by Jeff Grabill found that college students value texting more than they value all other written forms of communication — and that students value texting because “it’s fast, it’s efficient, and it’s second nature in an age of instant connectivity” A study out this month, led by assistant professor of education Christine Greenhow, documented that students who tweet as part of classroom learning are more engaged with their peers and with the instructor, and achieve higher grades The key was that the classes studied approached the integration of Twitter intentionally, using it as a tool to empower students to engage in information sharing, collaborative learning, brainstorming with the instructor in real-time, seeking real-time feedback from the instructor, and even texting with authors and researchers in the field. Twitter in the Classroom In our March 2011 article “Twitter in the Classroom,” Academic Impressions interviewed experts such as Ray Schroeder, professor emeritus and […]

Survey Report: Online Giving, Mobile Apps

Market research firm IDC projected last year that by 2015 in the US, more people will access online content through mobile devices than through wired Internet connections, and many institutions are reporting sharp increases in the web traffic they are seeing from mobile devices. For example, Brett Pollak, director of the campus web office for the University of California, San Diego, reported that over the past two years, UCSD has seen an average increase of 0.5% each month in the number of website views from mobile devices. Now, nearly 20% of their web traffic (counting both prospective students, current students, and alumni) is from a mobile device or tablet. Curious to see how the majority of shops are responding to this increase in student and alumni reliance on mobile technology, we conducted an informal survey this month of annual giving and alumni relations professionals. The results are indicative of a gap between the technologies alumni are using to interact with their alma mater and the technologies the alma mater is prepared to use in reaching out to its alumni. Key Takeaways From the Survey When asked what percentage of their fundraising dollars are received through online giving, nearly one third […]

Predicting Student Success: Rethinking GPA

In Academic Impressions’ recent edition of Higher Ed Impact: Monthly DIagnostic, “Success Leaves Clues: Predictive Modeling in Higher Education,” we interviewed a number of experts to provide a conceptual overview of how institutions can take steps toward a more rigorous mining of their current and historical student data to identify predictors not only of which students will be at-risk — but predictors of success. Learning the shared characteristics of persistent and academically successful students can drive more informed investments in your recruitment and enrollment efforts. This week, we wanted to isolate one of the “big” factors — GPA — and take a brief look at how you can take a more sophisticated look at high school GPA and first term GPA as predictors. For a few tips, we interviewed Bernadette Jungblut, West Virginia University’s director of assessment and retention, and Jim Scannell, president of Scannell & Kurz Inc. Here are some of the thoughts they shared with us. Rethinking High School GPA “Don’t just rely on overall high school GPA,” Jungblut warns, noting that often one’s first impulse is to isolate high school GPA as a more effective predictor than standardized test scores and other frequently-used indicators. But Jungblut suggests […]

A Data-Informed Approach to Student Retention

Few institutions are performing sophisticated predictive modeling on factors affecting student retention, and given how many factors there are (both within and outside the institution’s control), predictive modeling can appear quite daunting. But you don’t have to go from A to Z all at once. “Typically,” Jim Scannell, president of Scannell & Kurz Inc, advises, “we encourage institutions not to leap into predictive modeling immediately. Start by doing univariate analysis, collecting descriptive knowledge.” For example, out of an entire class, you could set out to describe: How many men retain versus women? How many men versus women achieved higher than a 3.0 GPA? How did your transfer students from two-year institutions perform versus your transfer students from four-year institutions? Students from public versus private high schools? Student cohorts based on race? Suppose you find that men in that class are, on average, achieving a lower GPA than women. Can you dig deeper? For example, if you have strong athletics, compare both the academic preparation of entering athletes versus non-athletes and the academic success of those two groups during the first year. Do you have a lower GPA for male students because you enrolled 100 football players who were less academically […]

Data-Informed Recruitment and Enrollment

Moving beyond high school GPA and standardized test scores, you will want to look for predictors of student success and affinity for your institution by analyzing data on your past and current students at each stage of their relationship with your institution. Identify shared characteristics of those students who model behaviors you want to encourage. Look for shared characteristics among: Prospects who apply (versus prospects who don’t) Admits who enroll Students who take leadership roles Students who perform high academically Students who persist into the second year Students who graduate within a certain time range Students who stay engaged with the institution after graduation and take leadership roles in the alumni community Once you know the characteristics of your current, most successful students, these characteristics become additional attributes that you can identify in your recruiting process. Suppose that your data indicates that a significant percentage of the students who show high academic performance and persistence in your engineering program took calculus prior to entering it—and you find that many of these are transfer students who completed calculus while enrolled at a local community college. With this knowledge, you can look to your applicant pool and identify applicants who have taken […]

Success Leaves Clues: Predictive Modeling in Higher Education

by Amit Mrig

Included in This Report: October 2012. Given increasing competition, shifts in student enrollment, and reduced resource levels, it’s critical that colleges and universities recruit and retain the students who are most likely to succeed at their institutions. By reviewing data on current and past students and alumni, and engaging in predictive modeling, you can identify not only the factors that impede desired outcomes such as yield, student retention, and alumni engagement and giving rates, but also the positive factors that contribute to those outcomes. In this edition, we have turned to institutional researchers, enrollment managers, and advancement professionals to highlight examples of predictive indicators and data-informed tactics for enrolling and supporting the right students and helping them transition into engaged, committed alumni. We hope their advice will be helpful to you. Read the report. See Other Topics in Institutional & Academic Planning

Mining Your Data: From Students to Alumni

Your institution has enrolled a strong class of students, and a high percentage of them have persisted and are thriving academically. Now it is the senior year. In a few months, these students will graduate, and, if you do not engage them proactively now, you will lose your best opportunity to invite them to engage with you and give back to the institution as alumni. A few figures to consider: According to Eduventures’ 2008 study Transitioning Donors to Higher Gift Levels, almost half of all donors make their first gift to the institution more than 20 years before making a contribution at the major gift level. According to the 2011 Capgemini and Merrill Lynch World Wealth Report, 32%—nearly a third—of high net-worth individuals (HNWIs) in North America are under age 55, an increase in the number of the young wealthy over previous annual reports. These data speak to the importance of cultivating donors as early as possible. And as affinity with your institution develops while alumni are still students, managing the student-to-alumni transition is especially critical. Key Indicators of Giving and Engagement What can you learn about preparing students to become engaged alumni, based on the data you have (or […]

Reviewing Your Data: What You Might Find

With scarce resources, it’s time to become increasingly savvy about the students you recruit and enroll, how you support them in ways that make a difference in their academic success and persistence, and how you approach the student-to-alumni transition. Success Leaves Clues Look at your past and current students and your current donors to identify indicators of retention, academic success, giving, and engagement. This entails identifying the shared characteristics of those students and alumni who are most successful and have the most pronounced affinity for your institution. Success leaves clues, and locating those clues can help you make better decisions at each stage of the student lifecycle, from recruitment, to retention, to graduation and transition to alumni. Predictive modeling based on current student and alumni data can inform your investments in recruiting, student support, as well as student philanthropy and young alumni engagement. [[{“type”:”media”,”view_mode”:”media_large”,”fid”:”1405″,”attributes”:{“alt”:””,”border”:”0″,”class”:”media-image” ]] “Predictive modeling is a powerful statistical tool because it isolates those statistically significant variables that really drive the behavior of students—to find out of all the students who inquire, who will apply; or of admits, who will enroll; or of those enrolled, who will stay or who will leave.” Jim Scannell, President, Scannell & Kurz […]

DFW Rates and You: Rethinking Support for At-Risk Students

In a recent interview with Academic Impressions, Bernadette Jungblut, West Virginia University’s director of assessment and retention, noted with some dismay that too frequently institutions have used data on individual courses’ D/fail/withdraw rates primarily as a means of performance evaluation for faculty, rather than partnering with faculty in taking a closer look at the DFW rates for clues to identify specific challenges students are having. Jungblut suggests that historical and current DFW is a particularly effective indicator that can be used to inform proactive rather than punitive action. Indeed, many institutions have begun identifying students taking courses with high DFW rates as “at risk.” On one level, this is a useful move — if it prompts both faculty and those charged with student retention to monitor real-time, operational data on students in those courses closely. But this is only a preliminary move, taking a “broad brush stroke” approach to tracking the students taking these courses. With a limited amount of digging into student data, it’s possible to take a much more sophisticated and effective approach to identifying and supporting at-risk students in high-DFW courses. Jungblut offers these ideas. Taking a Closer Look at Your Data Have you looked at your […]