Originally presented at the 40th Annual Conference on the First-year Experience

1. Designing Early Alert Programs
Aimed at Fostering Student
Success and Persistence
Mike Dial
University Advising Center
University of South
Carolina
Paige McKeown
University Advising Center
University of South
Carolina

2. Agenda for
Our Time Together
• Welcome and Introductions
• Defining Early Intervention
• History, Purpose, and Value of Early Intervention
• Early Intervention on the National Landscape
• Theoretical Underpinnings
• Mission and Goals
• Identifying Red Flags at Your Campus
• Drafting Intervention Plans
• Assessment
• Conclusions

3. Learning Outcomes
• Understand the history, purpose, and value of early alert programming
• Explore recent research/data on the national landscape of early alert
programming
• Identify key components for early intervention at their institutions
• Design and facilitate a systematic early alert program
• Develop and sustain a network of faculty and staff dedicated to
supporting students at various bottlenecks in the first-year experience.
• Prepare faculty to monitor student behaviors predictive of negative
academic consequences
• Prepare student support staff to respond and intervene with flagged
students
• Evaluate and assess early alert programs for continued improvement

4. Action Plan Workbook

5. Background
What do we mean by
“Early Alert” or “Early
Intervention”?

6. “A systematic method of
recording and communicating
student behaviors that
contribute to student
attrition” and “effective
intervention at the first
indication of academic
difficulty.” (Tampke, 2013)

7. RET = E ID + (E + IN + C) IV
(Seidman, 2012)

8. Collaboration and Communication
• Who is involved?
• Who should be involved?
• What systems exist to allow
communication
Advising
Student
Success
Centers
Housing
Financial Aid
Emergency
Aid Programs
Peer Mentors
First-Year
Seminars
Gateway
Courses
Orientation
Writing
Intensive
Courses
Career Centers Counseling

9. Brief History of Early Alert

10. Rationale
• Pushback against ”Academic Darwinism”
• Belief that intervention can make a
difference

11. Implications
• Monitor all students and not
just those that enter at-risk
• High-touch, high-impact
interventions model care
promised in admissions and
orientation

12. Causes
• What are the immediate
signs
Proximal
• What are the factors
behind the immediate signs
Distal
• Ask 5 “Whys”
• Build relationships of trust
Tips to get to
the root cause

14. Research & Best Practices
• Limited
• Single Institution Studies
• Accessibility/Ease of Use for Practitioners

15. Prior National Surveys

16. 2017 National Survey on The First-
Year Experience
• Administered Feb – Aug 2017
• 3,977 Institutions invited to participate
• 537 responses (13.5% response rate, lower than
anticipated)
• Often the VPSA or the person most responsible for first-year
programs
• Covers broad range of initiatives designed to support
success in the first college year
Young, D. (2019)

17. Most Common FYE Programs/Initiatives Freq. %
First-year academic advising (ADV) 422 80.4
Early alert systems (EA) 415 79.0
Pre-term orientation (OR) 396 75.4
First-year seminars (FYS) 386 73.5
Placement testing (PT) 346 65.9
Peer education (PE) 327 62.3
Student success center (SSC) 290 55.2
Developmental education (DEV) 286 54.5
General education (GE) 284 54.1
Convocation (CNV) 276 52.6
Notes: n = 525.
Young, D. (2019)

18. No "Perfect" Professional Home
• On Campus
• In the Professional
Organizations
• NODA
• FYE
• NACADA*

19. Prevalence
• Two Year: 64.2%
• Four Year: 83.6%
• Public: 77.2%
• Private: 82.0%
Young, D. (2019)

20. Students Targeted
Which types of first-year students are monitored through an early
warning/academic alert system? Freq. %
All first-year students 291 76.0%
Other, please specify 49 12.8%
Students on academic probation 26 6.8%
Student athletes 24 6.3%
Students enrolled in developmental or remedial courses 17 4.4%
Students with at-risk factors such as GED, low ACT scores, etc. 14 3.7%
Students eligible for federal or state equal opportunity programs (EOP) 11 2.9%
Provisionally admitted students 10 2.6%
First-generation students 7 1.8%
Learning community participants 7 1.8%
Science, technology, engineering, and math (STEM) students 7 1.8%
Young, D. (2019)

21. Students
Targeted
• Differences by Institution
Characteristics
• Two-year: Developmental
education, Other
• Four-year: All first-year students
• Public: Student athletes, students
on probation, other
• Private: All first-year students,
students at risk

22. Reach
10%
or
less
11-
20%
21-
30%
31-
40%
41-
50%
51-
60%
61-
70%
71-
80%
81-
90%
91-
100%
Two-year 16.9% 9.9% 16.9% 11.3% 8.5% 4.2% 5.6% 4.2% 2.8% 19.7%
Four-year 7.7% 10.3% 11.9% 7.1% 5.4% 3.5% 3.2% 4.2% 6.7% 40.1%
0%
10%
20%
30%
40%
50%
Percentage
of
Institutions
Percentage of First-Year Students Reached
Young, D. (2019)

23. Reach
10%
or less
11-
20%
21-
30%
31-
40%
41-
50%
51-
60%
61-
70%
71-
80%
81-
90%
91-
100%
Public 11.1% 12.0% 14.8% 8.8% 7.4% 4.2% 4.2% 3.7% 4.6% 29.2%
Private 7.3% 7.9% 9.7% 6.7% 4.2% 3.0% 3.0% 4.8% 7.3% 46.1%
0%
10%
20%
30%
40%
50%
Percentage
of
Institutions
Percentage of First-Year Students Reached
Young, D. (2019)

24. Communication and
Intervention
Calendaring

25. Timing
• How “early” is “Early Alert”?
• Midterm?
• First signs of issues?
• Between terms?

26. Timing
Only before
midterm
Only at or after
midterm
Ongoing
throughout the
term
Ongoing
throughout the
first year
Other
Two-year 8.5% 1.4% 46.5% 38.0% 5.6%
Four-year 7.1% 6.7% 22.8% 57.4% 6.1%
0%
10%
20%
30%
40%
50%
60%
Percentage
of
Institutions
Timing of Monitoring or Response of Early-Warning or Academic Alert System
Young, D. (2019)

27. Timing
Only before
midterm
Only at or after
midterm
Ongoing
throughout the
term
Ongoing
throughout the
first year
Other
Public 9.3% 6.0% 28.2% 50.0% 6.5%
Private 4.8% 4.8% 25.5% 59.4% 5.5%
0%
10%
20%
30%
40%
50%
60%
Percentage
of
Institutions
Timing of Monitoring or Response of Early-Warning or Academic Alert System
Young, D. (2019)

28. 89.0%
89.0%
83.0%
74.0%
53.0%
52.0%
27.0%
11.0%
89.6%
88.3%
68.0%
54.8%
43.6%
41.8%
22.7%
15.1%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
Faculty Academic
Advisors
Academic
Support
Personnel
Athletics
Department
Staff
Counseling Residence Life
Staff
Peers Information
Technology Staff
Types of Staff Participating in Early
Alert/Academic Warning Programs
2012 JNGI 2019 NRC
Barefoot, B. O., Griffin, B. Q., & Koch, A. K. (2012)
Young, D. (2019)

29. Relational Intervention
Effective intervention should be
facilitated by institutional staff
with the closest relationships to
at-risk students.
At-Risk
Student
Academic
Advisor
Seminar
Instructor
Athletics
Advisor
Program
Advisor
Honors
Advisor

30. Academic Advisors and Early
Alert Academic advisors responding
to early alerts benefit students
by:
• Connecting them to
resources
• Ensuring they are in majors
and courses that align with
their strengths, values, and
goals
• Showcasing an institutional
ethic of care for students and
their success.
This Photo by Unknown Author is licensed under CC BY-SA-NC

31. Session 2
Technology, Theory, and Real-World Interventions

32. Session 1 Recap
• “A systematic method of recording and communicating student behaviors that contribute to student attrition” and
“effective intervention at the first indication of academic difficulty.” (Tampke, 2013)
• RET = E ID + (E + IN + C) IV
• High quality early alert programs can improve equity on campus for students in “graduation gap” populations
• Best Practices
• Systematic, collaborative approaches
• Primary intervention agents = full-time staff with existing relationships to students (academic advisors, athletics
advisors, program advisors, seminar instructors, etc.)
• Referrals/alerts should be available throughout the academic year
• Early alert programs should target all students, not just those in specific populations/courses

33. Role of Technology

34. Role of Technology
Unable to
judge
1 - Entirely
technolog
y-based
2 3 4 5 6
7 -
Entirely
human-
based
Series1 3.1% 1.3% 5.2% 7.3% 24.0% 14.4% 14.1% 30.5%
3.1% 1.3%
5.2%
7.3%
24.0%
14.4% 14.1%
30.5%
0%
5%
10%
15%
20%
25%
30%
35%

35. Data Collection
• Precollege Data
• Student Self Reports
• Survey Responses
• Faculty submitted grades and/or
attendance
• Learning Management System Analytics

36. Role of
Technology
In other words, sending up a red light isn’t likely
to influence retention. But if that red light leads
to advisers [or other student support personnel]
reaching out to students and providing targeted
support, we might see bigger impacts on student
outcomes.
(Karp, 2014)

38. Intrusive Advising
• Action-oriented
model
• Identification of
students at “crisis
points”
• Connections to
resources when
most appropriate
Earl, 1987

39. 3 Postulates of Intrusive Advising
1. Faculty and staff can be
trained to identify students
who need assistance
2. Students DO respond to direct
contact in which their
concerns are identified and
help is offered
3. Deficiencies in a student’s “fit”
can be treated
(Earl, 1987)

40. Choice Architecture
A choice architect has the responsibility for
organizing the context in which people make
decisions.
(Thaler and Sunstein, 2009)

41. Choice Architecture
Poor Choices
• Inexperienced
• Poorly Informed
• Slow or Infrequent
Feedback
Good Choices
• Experience
• Good information
• Prompt Feedback
(Thaler and Sunstein, 2009)

42. Help Seeking
• An important developmental
skill
• Unique among learning
strategies

43. Transtheoretical Model (TTM) of Intentional
Human Behavior Change
(Miller and Rollnik, 2012)
Pre-contemplation
Contemplation
Preparation
Action
Maintenance
Relapse

44. Types of Pre-
Contemplators
• Reluctant
• Lack of knowledge/do not want to consider change
• Rebellious
• Aware of the problem
• Often invested in the problem/problem behavior
• Invested in making their own decisions – “don’t tell me
what to do”
• Resigned
• Lack of energy or investment
• Given up on the possibility of change
• Overwhelmed by the problem
• Rationalizing
• Appears to have all the answers
• Not considering change because of personal risk
• May believe their problems are someone else’s fault

45. Breakout Rooms
• What theories or approaches currently guide
your early intervention initiatives?
• What from today’s session do you want to
learn more about?
• What theories or approaches discussed
today do you see yourself wanting to
incorporate in your early intervention
planning/facilitation?

46. Ideas? Thoughts? Considerations?

47. What is Early
Intervention?
• Formal, proactive feedback systems
that alert students and staff to red
flags.
• (Cuseo, n.d.)

48. Signals for Early Alert
• Academic performance
• Behavior
• Disruption in class
• Skipping class
• Conduct
• Affect
• Others?

49. Class Attendance = Highly Predictive of
Persistence
1.98
2.96
0
0.5
1
1.5
2
2.5
3
3.5
Average First-Year GPA
More Than Three Absences in One Classs No Attendance Problems
64%
89%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Retention to Sophomore Year
More Than Three Absences in One Class No Attendance Problems
http://www.pathfinders.msstate.edu/findings.html

50. Early
Intervention
Red Flags at
Carolina
Non-registration in upcoming term
Faculty submitted “at-risk” progress reports and alerts to advisors
Attendance
Registered in fewer than 13 credit hours
Holds – (more info coming)
Bursar Drop for Non-Payment
Scholarship Risk
Student Survey Response

51. The Non-Registered Initiative
Advisors and key department contacts receive a list of
students who are eligible to enroll in the coming semester,
but aren’t
Graduating students are removed
Advisors leverage existing relationships to support students in registration barriers
Advisors’ lists include if students have advising holds and other registration holds that may identify the barrier
Advisors encourage the student to register and document reasons students are not returning (if they know)

53. Holds prevent students from
registering on time
Student resolves hold but
misses first choice classes
Failure to sequence classes correctly
increases time to degree
Student in classes in which
they are less likely to succeed
academically
Additional semesters
increase college cost,
academic difficulty
decreases GPA
Student resources, perseverance, and
academic self-efficacy exhausted before
degree completion
Hold “Death Spiral”
(Venit, Mason, & Hlavac, 2009)

54. First-Year
Retention
Survey
39 question survey
distributed to all
new FTIC students
each fall
Covers six categories
• Academic Behavior
• Adjustment
• Community and Living
• Finance
• Resilience
• Other
Institutional
Research identifies
predictive questions
Collaborative
Response Team

55. The Water Cooler
• Questions
• Comments
• Thoughts

56. Session 3

57. Developing Goals for Your Early Intervention
• Starting with the end in mind helps create
cohesiveness and buy-in
• Lean on your institutional and/or unit mission
statement
• Starting with an established mission helps
define vision-inspired goals, value, and
impact
• Goals should…
• Detail how the program aligns with the
mission
• Detail overarching expectations
• Reflect the operation efforts of early
intervention

58. Questions as
You Develop
Goals
• What’s the purpose of
your program?
• What need are you
trying to fill on your
campus?
• What are your intended
outcomes?
• Who is your student
population
(institutional,
departmental, or
program)?
• Who are your
stakeholders?
• How will your program
impact those
stakeholders?
• When are monitoring of
students and
interventions going to
occur?

59. Proactive vs.
Reactive
• Both are valid!
• Must serve your target population(s) and
identified red flags/crisis points
• Proactive interventions may be geared towards
“historically” at-risk populations
• Help to preempt and support students
through acclimation challenges
• Most early interventions ARE reactive
• Based on a referral/alert or concerning
behavior

60. Drafting the Intervention
Plan – Who?
WHAT RESOURCES ARE
AVAILABLE TO YOU AT
YOUR CAMPUS?
WHO ARE YOUR
STAKEHOLDERS/
COLLABORATORS?
WHO WILL BE YOUR
ALLIES?
BIGGEST
CHALLENGERS?
WHO DO YOU NEED
BUY-IN FROM?

61. Winning Buy-In
Top Down
President
Provost
Deans
Chairs
Faculty
Grassroots
Faculty
Chairs
Deans

62. Return on
Investment
Low Medium High
Two-year 26.7% 18.3% 42.2%
Four-year 13.2% 18.3% 58.0%
0%
10%
20%
30%
40%
50%
60%
70%
Percentage
of
Institutions
Return on Investment
Young, D. (2019)

63. Drafting the
Intervention
Plan – Campus
Culture
• How do students engage with existing services
on campus?
• How do offices engage with each other?
• Who has existing, “assigned” relationships with
students?
• What services address the “red flags” on your
campus?
• How are students funneled to those services?
• What communication are students receiving
about these services?

64. Avoid Duplication and Overlap

65. Contact
• Email
• Letter (in 2021?)
• Text Message
• Phone
• Face-to-face
• Social media

66. Type of Response
96.6%
82.5%
62.9%
26.1%
9.4%
3.1%
0% 20% 40% 60% 80% 100%
Phone, letter, or electronic contact
Informed about assistance…
Contacted in person
Required to obtain assistance
Families were notified
Other
Percentage of Institutions
Types
of
Response
from
Early-Alert
Systems
Young, D. (2019)

67. Student Reaction
If students perceive early warnings
as a reprimand rather than an
opportunity to get help, they may
ignore the signals or avoid efforts
of college personnel to contact
them (Karp, 2014)

68. A Possible Model for Intervention/Communication
Active
Passive
Negative
(Punitive)
Informational
(Just the Facts)
Positive
(Motivational)
(Dial, 2020)

69. A Possible Model for Intervention/Communication
Active
Schedule Advising
Global Communications
Registration Holds Outreach
Caseload Scrub
Transfer Scrub
< 13 Credit hours
Non-Registered Initiative
First-Year Retention Survey
Passive
Registration Holds Probation Outreach Student Kudos
Negative
(Punitive)
Informational
(Just the Facts)
Positive
(Motivational)
(Dial, 2020)

70. Psychologically Attuned Communication
Describe academic challenges as a process of learning, not a label
Describe
Acknowledge factors that contribute to academic difficulty
Acknowledge
Communicate that is it not uncommon to face academic difficulty
Communicate
Offer hope and support
Offer
Waltenbury, M., Brady, S., Gallo, M., Redmond, N., Draper, S. & Fricker, T. (2018). Academic Probation: Evaluating the Impact of Academic Standing Notification Letters on Students.

71. Drafting Intervention
Plan - Technology
What does it need to
do?
•Pie-in-the-sky:
given your goals,
what would it
ideally do?
Would this
technology enhance
workflow, or
overcomplicate?
Do you have a
platform on campus
with this capability?
If so, how can
existing technology
be utilized
effectively?
If not – how can
existing technology
be used to fit your
needs?
Is piloting or scaling
an option if the
current tech doesn’t
fit your needs/goals?
Who are your
collaborators in
technology?

72. All the Choices!
• Complexity of modern colleges and
universities
• Proliferation of products
• Philosophy of student support staff
• Sources of information
• Modes of communication

73. •Strengths
S
•Weaknesses
W
•Opportunities
O
•Threats
T

74. Training Staff for Early
Intervention
Engage staff to be the subject
matter experts in their setting
Academic support
Counseling
Housing
Career services
Advising
Faculty
What training do staff need to
respond to the red flags?
Depends on which staff are
responding

75. Increasing
Faculty
Participation
Messaging during faculty orientation
Focus on first-year courses
Make the case with data
Encouragement from the provost
Periodic email prompts
Close the loop on reporting
Effective early alert has an opportunity
to be a great “equalizer”
Align faculty and staff in the
collaborative work of supporting
student success
(Venit, Mason, & Hlavac, 2009)

76. Referral Matrices
• Alerts staff to appropriate referral
• May go beyond traditional early
intervention to include student well-being

77. I Refer
Front
Back

78. Assessing Early
Intervention
“Assessment is the process of gathering and discussing
information from multiple and diverse sources in
order to develop a deep understanding of what
students know, understand, and can do with their
knowledge as a result of educational experiences; the
process culminates when assessment results are used
to improve subsequent learning”
- Huba and Freed, 2000
https://www.northwestern.edu/searle/assessment-of-student-
learning/assessment-process/index.html

79. Assessing
Early
Intervention
What data already exists on your
campus that would be useful to you in
early intervention programming and
assessment?
Utilize Schuh’s Eight Questions to
simplify the assessment process to a
manageable level

81. Thank You!
Mike Dial
mdial@sc.edu
miketdial@weebly.com
Twitter: @mtdial
Paige McKeown
paigem@sc.edu
Twitter: @paigecristine_m
Please
remember to
submit your
evaluation on
Guidebook!

82. Sources
Barefoot, B. O., Griffin, B. Q., & Koch, A. K. (2012). Enhancing student success and retention throughout undergraduate education: A national survey. Brevard, NC: John N. Gardner Institute for Excellence
in Undergraduate Education, Brevard, NC. Retrieved from
https://static1.squarespace.com/static/59b0c486d2b857fc86d09aee/t/59bad33412abd988ad84d697/1505415990531/JNGInational_survey_web.pdf
Cuseo, J. (n.d). Red Flags: Behavioral indicators of potential student attrition. [White Paper]. Retrieved from http://listserv.sc.edu/wa.cgi?A0=FYE-LIST
Dial, M., & McKeown, P. (2019, December). Beyond faculty referrals: Advisory facilitated early intervention. Academic Advising Today, 42(4). https://nacada.ksu.edu/Resources/Academic-Advising-
Today/View-Articles/Beyond-Faculty-Referrals-Advisor-Facilitated-Early-Intervention.aspx
Habley, W. R., Bloom, J. L., & Robbins, S. B. (2012). Increasing persistence: Research-based strategies for college student success. John Wiley & Sons. San Francisco: Jossey-Bass.
Miller, W. R., & Rollnick, S. (2012). Motivational interviewing: Helping people change. Guilford press.
Seidman, A. (2012). Taking action: A retention formula and model for student success. In A. Seidman (Ed.), College student retention formula for student success (pp. 267–284). Rowman & Littlefield
Publishers.
Tampke, D. R. (2013). Developing, implementing, and assessing an early alert system. Journal of College Student Retention: Research, Theory & Practice, 14(4), 523–532.
https://doi.org/10.2190/CS.14.4.e
Thaler, R. H., & Sunstein, C. R. (2009). Nudge: Improving decisions about health, wealth, and happiness. New York, NY: Penguin.
Venit, E. P., Mason, J., & Hlavac, M. (2009). Hardwiring student success: building disciplines for retention and timely graduation. Washington, D.C.: Education Advisory Board, Advisory Board Company.
Waltenbury, M., Brady, S., Gallo, M., Redmond, N., Draper, S. & Fricker, T. (2018). Academic Probation: Evaluating the Impact of Academic Standing Notification Letters on Students.
Winfield, J. (2018, December). The art of intervention: Partnering with faculty for early academic alert. Academic Advising Today, 41(4). https://nacada.ksu.edu/Resources/Academic-Advising-
Today/View-Articles/The-Art-of-Intervention-Partnering-with-Faculty-for-Early-Academic-Alert.aspx
Young, D. (Ed.). (2019), 2017 National Survey on The First-Year Experience: Creating and coordinating structures to support student success. Columbia, SC: University of South Carolina, National Resource
Center for The First-Year Experience & Students in Transition.