Coordinated Support: Using a Range of Activities to Enable Personalized Learning

At Rio Salado Community College we're working on several major initiatives to deliver personalized learning experiences to our students. A student's experience at Rio Salado spans the academic affairs side and the student affairs side, and we define personalized learning as "meeting students where they are." First we identify what students need, and then we provide key interventions or targeted outreach to help them succeed. A two-year grant funded the student experience efforts through 2015.

RioAchieve

A grant from the Bill & Melinda Gates Foundation funded an initiative known as RioAchieve, for which we actually created five different interventions to help personalize the student experience.

RioCompass

We created a student completion portal, called RioCompass (figure 1). Within that portal students can identify their goals and program of study and can indicate whether their plan targets a career or involves transferring to a four-year institution. From there they create a personal academic plan to meet their unique needs in reaching their goal.

Within the portal students have a personal advisor assigned to them, as well as a peer mentor. They can upload transcripts and interact with the advising team. We created task lists to make sure of keeping students on track. If they need to take a placement exam or submit financial aid paperwork, reminders alert them of the required actions. Some automated triggers occur, and students have some opportunities to generate their own task reminders. Really, the portal focuses on persistence and completion, providing a one-stop shop of information.

Student Help Desk and Peer Mentors

Alongside the portal, the advising team and peer mentor team created a student help desk, which has a ratio of about 500 students per advisor and about 800 students per peer mentor. It applies an intrusive advising approach, with a lot of outreach to make sure that students persist in their courses and that we retain them within the program, help them enroll for the next term, or answer questions. Many of the peer mentor interactions involved study skills and having a backup plan.

A help desk is often reactionary, and we wanted our advisory help desk to be proactive. When the initiative began, the advisors received assignments for specific students within the grant cohort. These were first-generation college students, Pell eligible, and seeking a degree. The advisors did outreach daily to approximately 50 students, based on whether a student wanted phone or e-mail contact. Based on student preferences, advisors reached out to other students on a monthly basis, putting them in a queue instead of waiting for the student to contact them. The Student Success Team provided proactive outreach and nudges to assist the students.

The peer mentors were all housed in the same area, called the “RioAchieve hub.” This allowed for the help desk to be a collective team. If there were questions, there was a resource only a few feet away. Peer mentors had extensive training, including in FERPA. Peer mentors were trained to provide tips and strategies related to student skills and time management. The peer mentors could share their experiences related to college success. This seemed to be the right connection for many students. The students reached out to chat with their peer mentors, and in some instances, students reached out more to their mentors than the advisors.

Guided Evaluation and Assessment Response System

Using the guided evaluation and response system (GEAR) and its robust rubric, instructors create best practices and effective feedback from in-time instruction to additional resources. The information is shared across disciplines by means of a repository to which all of the instructors have access. They can pull from the repository and then copy and paste information into feedback on student assignments. Those students receiving instructor feedback said it was just the right amount, motivated them to continue to submit assignments, and helped them improve their assignments.

We noticed a strong linear correlation between the students who read the feedback — obviously, not all students do — and their overall grades. Those students who consistently clicked on the instructor feedback earned A’s and B’s in the courses, while those who rarely read the feedback usually got C’s and D’s.

We also had this odd anomaly of students who constantly clicked on the feedback and yet failed the course. Either they were not understanding the feedback, or they weren't really sure how to apply it.

The feedback repository also included robust resources if students either misunderstood the material or lacked knowledge. Beyond just providing resources, a “mini teach” could be provided for the student. The mini teach may present the content in a new way and allows for the iterative learning process to be embedded in feedback.

The one drawback is the technology that currently houses the feedback, resources, and mini-teach. We found that it could be time consuming for instructors, and there is a learning curve with implementation. We are currently working on GEAR 2.0 to improve the feedback, usability, and personalization for instructors.

RioPACE

RioPACE is our predictive analytics model. It has actually been around for about eight years, and we continually improve the model’s accuracy. There are many predictive analytics tools out there, but this is something we created in-house. It looks at three behavioral components:

• Log-ins: How often the student is logging into the course?
• Site engagement: Are they clicking on lessons? Reading instructor feedback? What are they doing once they get inside the course?
• Progress: How often are they submitting assignments? How many points are they earning on those assignments (points earned versus points possible)?

We do a comparison of the students who are currently enrolled versus historically successful students. These comparisons provide a success prediction, which is displayed with the PACE icon. The icon is a green, yellow, or red indicator depending on a student’s behavior. The model informs the student whether they are on track for success, falling behind, or need improvement on the basis of each of the above criteria. Instructors and students have a view of the PACE icon. Instructors can see a student’s PACE status in their grade book, allowing easy  identification of students who have a red or yellow PACE icon. This creates an outreach opportunity from the instructor. They will try to provide additional feedback, resources, or tutoring opportunities for the students.

Students can view their PACE icon from their course homepage. We also discovered that for a lot of students, the indicators served as triggers to communicate with their instructor. They seem to reach out more, based on their PACE icon. If it was red or yellow, or they noticed it had shifted, the response was often immediate — they would e-mail the instructor and ask how to get back on track. The model provides an opportunity for students to modify their behaviors and work toward success.

We surveyed over 100 students and approximately 80% would prefer to enroll in a course that utilizes the PACE model and icon.

Guided Intervention and Response

GIvR, Guided Intervention and Response, is our early-alert management system. What makes GIvR different from other early-alert systems is that we rely on several automated triggers. We touched base with several departments across the college, from faculty, to student affairs, counseling, the library, and our advising team. We asked the various departments what factors impede student success. Textbooks, placement exams, not enrolling in the correct courses, PACE status, and technology issues were top on the list.

Triggers aligned to these issues were automated. Key individuals across the college receive an alert and are accountable to reach out to the student and resolve the issue rather than pass the student around from department to department. This allows a one-stop early-alert system. We try to intervene as early as possible — the earlier the better.

An example of an automated trigger would be a student who tested in to a developmental education course but has not enrolled yet — that would create an alert to the advisor. Rio has both an instructional and a technology help desk; if a student calls two or three times to either or both departments, this would be an alert they are struggling with the system. An alert would be generated, and  an intervention opportunity is presented. This allows the college to be proactive in outreach and identify systemic issues that perhaps would be missed otherwise.

If a student’s PACE indicator in two or three course changes, this creates an alert to both an advisor and our instructional help desk. The PACE icon change can also create an alert for tutoring, who will reach out to students to offer them or remind them about tutoring services. We have virtual and in-person tutoring.

Many of the alerts and interventions occur within the college and prompt proactive outreach. However, we also create student alerts and reminders. For example, if students have not taken a placement exam or uploaded their transcripts, the system will create a task in the student completion portal reminding them top complete these tasks.

GIvR rolled out in the fall of 2015. This is a change in our processes and outreach. At this point, we do not have data to support the effectiveness of the interventions, but we are hopeful! We do know that the earlier institutions can identify at-risk students and intervene, the more likely institutions can change the students’ trajectory, get them back on track, and improve their odds of success.

Results

The grant has run two years. We wrapped everything up in 2015 and will continue to track the grant cohort students over a five-year period. Over the two years, we enrolled about 6,000 students into the grant cohort. About 3,600 are still actively enrolled, and we've been tracking their persistence and academic success against a comparable cohort drawn from 2011 data (students met the same criteria: new to the college, awarded Pell grants, and seeking a degree). The RioAchieve persistence rate semester-to-semester shows an average increase of seven percentage points, and year-to-year persistence shows an average increase of four percentage points, over the historical control cohort. The grant population also shows slight increases in course retention, success, and grade point averages. Tables 1–3 summarize some of these results.

Table 1. Semester-to-semester persistence

Reporting Date	First Term (N)	Second Term (N)	Third Term (N)	Fourth Term (N)	Fifth Term (N)
Comparative Cohort	4,154	1,315 (31.7%)	775 (18.7%)	496 (12.0%)	381 (9.2%)
January 2015	2,713	682 (40.0%)	269 (25.0%)	n/a	n/a
September 2015	3,483	980 (38.8%)	401 (23.6%)	199 (18.7%)	n/a
January 2016	3,849	1,105 (38.2%)	602 (23.9%)	295 (17.6%)	159 (15.1%)
September 2016	n/a	n/a	n/a	n/a	n/a

Table 2. Course retention and success

Reporting Date	Course Retention (Grade A, B, C, D, F)	Course Success (Grade A, B, C, P)
Comparative Cohort	88.9%	46.8%
January 2015	90.3%	51.8%
September 2015	91.0%	52.2%
January 2016	90.7%	53.6%
September 2016	n/a	n/a

Table 3. Overall academic success (average GPA)

Reporting Date	First Term	Second Term	Third Term	Fourth Term	Fifth Term
Comparative Cohort	1.19	1.96	2.43	2.47	2.66
January 2015	1.69	2.26	2.59	n/a	n/a
September 2015	1.67	2.33	2.52	2.52	n/a
January 2016	1.67	2.34	2.53	2.61	2.41
September 2016	n/a	n/a	n/a	n/a	n/a

Future Work

We recently were awarded one of the First in the World grants from the U. S. Department of Education. It's a $2.7 million grant and is focused along the same lines as the personalized learning initiative. We are looking to identify students based on similar criteria — at risk, new to college, Pell eligible, and program seeking. As soon as the students are identified, they are placed into a student success seminar. It goes over setting goals — helping them create their plan for academic success — and metacognitive skills like grids, resiliency, and the growth mindsets. They are also provided a PLUS facilitator. The grant is called PLUS (PLan for Undergraduate Success), and the PLUS facilitator is the one point of contact who can really help students with metacognitive skills, test taking, and time management. The facilitator will stay with the students through a focused sequence of courses.

We identified 13 credits across 11 courses that would meet the designations for multiple degree areas. These courses were chosen due to high enrollment for degree completion and their high students success rates. The idea is that by placing them in these courses their first semester — or, if they are part-time students, their first year in college — we build their confidence because they are likely to be successful in these courses. The following year, we will identify new Rio students who are seeking degrees and implement the same initiatives and interventions, but we will offer the focused sequence of courses and student seminar in an adaptive platform.

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Shannon McCarty serves as the dean of Instruction and Academic Affairs at Rio Salado Community College. Prior to her interim role as dean, she held the Physical Science Faculty Chair position. During this time, she began teaching online classes and has 10 years of online experience. She was responsible for hiring, mentoring, and supervising over 80 online and in-person instructors; additional responsibilities included developing online courses and assessments. McCarty worked closely with Rio Salado's Institutional Research Department to develop and implement RioPACE, a predictive analytics system. She earned her bachelor's degree in Biology and Chemistry from the University of Arizona and earned a master's in Educational Leadership from Arizona State University. In 2012, she completed her PhD at Capella University.