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Personalization at Scale: Using Metrics to Improve the Student Experience

 

The EvoLLLution | Personalization at Scale: Using Metrics to Improve the Student Experience
Institutions can improve their engagement with adult students by focusing on collecting and analyzing data analytics, which in turn can have a significant impact on student outcomes and success.

The first installment of this series, Personalization at Scale: Two Institutional Journeys, described the similarities and differences between two adult-serving online institutions, and the organizational capacity for leveraging data and technology to support learners.

UMUC and Capella are continuously exploring how data analytics can identify and support learners’ needs, especially in the first term, to set them up for success. Both UMUC and Capella use internally developed and third-party tools as part of this process, and both also leverage the learning management systems (LMS) that their institutions use to deliver orientation and similar courses. By using the same LMS that is used for academic courses, learners have the opportunity to become familiar with the technology that they will use throughout their degree program.

Capella: Current State

Capella University’s adult learners bring diverse academic, professional, and life experiences to their respective programs. To identify the academic and non-cognitive skills and abilities that learners possess, they complete an assessment during the onboarding process. This assessment data is used by learners, faculty and staff, and the university to support learner success.

The assessment evaluates learners’ skills and experience in categories that are critical for success in an online higher education program. Based on assessment results, new learners are provided with an online Personalized Skills Inventory report that provides self-paced resources to support them as they develop their areas for improvement and refine their areas of strength. These resources are aligned with the domains that are evaluated in the assessment, including technical readiness, goals and motivation, academic writing, self-management, and identifying a support network. The self-paced resources, in turn, provide another level of learner self-assessment to further identify the specific areas of strength and opportunity within these domains. As an example, based on the initial assessment, a learner may receive a recommendation to complete a self-paced time-management resource. Within this module, the learner is provided with another short self-assessment to further identify the specific aspect of time management that he or she may want to develop. This may include overcoming procrastination, using a scheduling tool more effectively, or adjusting levels of engagement in non-work activities to make time for coursework.

In addition to matching learners with Personalized Skills Inventory resources, assessment results are also used to provide new learners with an online orientation course based on their prior academic experience and skills, the degree program that they are enrolling in, and their non-cognitive skills. Capella University developed its asynchronous online orientation course based on institutional research and a review of the literature. Within the orientation, learners complete assignments and participate in online discussions with other new learners and Capella staff. The assignments and discussions provide learners with an opportunity to reflect on their areas of strength and opportunity as identified by their assessment results and develop a plan for leveraging resources for development. To best prepare learners for success, completion of the orientation course is a requirement for some new learners based on their assessment results.

Beyond the Personalized Skills Inventory and orientation, assessment data may also be used to create a personalized pathway for learners into their first academic program course. One specific example is the use of writing assessment results, used by some programs to provide a differentiated first academic program course by way of providing prescriptive writing resources to new learners with greater writing development needs. These writing resources are built into the course content and LMS to link the development of writing skills with the discipline-specific content of the course. Faculty teaching these courses have access to learners’ writing assessment results, allowing them to provide additional writing support when appropriate.

UMUC: Current State

As part of a comprehensive undergraduate onboarding initiative at UMUC, a four-week online onboarding course—CAPL 101: Creating Your Learning Plan (also known as “Jumpstart”)—was created to help new students create a personalized learning plan, focusing on assessment of skills and personality variables related to success in higher education and online learning as well as clarification of life and education goals. The course is designed to provide learners with a more personalized experience focused on their needs The project considered evidence that term-to-term reenrollment is a positive indicator of degree completion, that early success is a significant factor in adult student retention, and that students need non-academic skills to successfully complete their degree.

A unique aspect of the course is the problem-solving model in which it is embedded. Students develop their own best pathway through more intentional academic planning, informed by personalized feedback about their own strengths and weaknesses. This approach includes the integration of goals into a learning plan, leveraging diagnostic and planning tools to help students identify their individual areas of strengths and concerns, and exploring best options for each individual—both academic and personal—to support those goals while identifying strategies to mitigate risks.

One of the tools Jumpstart uses is the SmarterMeasure diagnostic to help students self-assess their readiness for online learning. This is integrated with other self-assessments to establish well-grounded career and academic goals. The assessments help students to create a learning plan that is the main deliverable in the course, along with a three-semester course plan. The learning plan comprises two parts: a personal baseline and an action plan. The personal baseline addresses strengths, abilities and traits, academic and online learning readiness, and academic and professional credentials. The action plan includes a personal mission statement, professional and academic goals, time management strategies, potential pitfalls and challenges with a strategy to prevent or avoid them, identifying a support system, and a check-in plan. The three-semester course plan is integrated into the Student Information System and is also visible to academic advisors. The course plan can be pre-populated with outstanding course requirements and includes direct links to register for courses in the plan, which can be modified by students at any time.

The use of data from the SmarterMeasure focuses on areas adult students often struggle with, such as motivation, procrastination, time availability and management, locus of control, and willingness to seek help. Students are asked to list their strengths, areas to improve, and strategies for making improvements. The course addresses both student needs and longstanding faculty and administrative concerns about learner readiness, especially for online learning.

Results: Capella

From analysis of a pilot implementation of the Personalized Skills Inventory report and self-paced resources, an asynchronous, staff-facilitated orientation course, and prescriptive writing resources embedded within academic courses, Capella has observed that learners who used these resources have demonstrated an increase in early course persistence and learning outcomes.

Based on these results, Capella University has scaled the Personalized Skills Inventory report and self-paced resources and orientation course to all new learners and degree programs. Feedback from learners, faculty and staff is reviewed and evaluated on an ongoing basis to optimize the orientation experience to continue to meet the needs of new online learners. Additionally, other academic programs within the university have implemented similar approaches to using writing assessment data to provide differentiated writing resources to support learners in developing this critical academic skill.

Results: UMUC

The most consistent effect of CAPL 101 is on the one-year retention rate and rate of re-enrollment into the next consecutive term compared to a matched student group. Students also demonstrated statistically significant increases in problem-solving knowledge as measured by a pre-test and post-test in the course. While the initial research shows correlation with positive outcomes, it did not determine the role of student motivation or explore which students might most benefit from the experience, since the majority of students opt into the class. In fall 2015, a randomized, quasi-experimental study with new applicants will further explore the course’s relationship to successful course completion and term-to-term re-enrollment. The results will be used to determine whether the course should continue and be expanded to more students—and possibly to identify target groups who would most benefit.

Future State: Capella

The use of assessment data has provided Capella University with the opportunity to provide learners with a more personalized early learning experience leading to increased persistence and learning outcomes. Learner assessment data continues to shape the university’s initiatives to support learners’ success and outcomes. With this goal as a unifying vision, the university continues to identify ways in which it will act on this data to provide personalized resources at other stages of the learner lifecycle. Doing so ensures that learner-generated data is used to best support learners as they pursue their educational goals.

Future State: UMUC

A model being implemented at UMUC, developed in partnership with Civitas Learning, scores and groups applicants based on their probability of enrolling in and successfully completing a first class at the university. This will enable the university to personalize pathways for entering applicants—for example, to develop specialized support for students who lack prior academic work or have weaker academic records, guidance on particular programs, or more individualized information on financial aid. In the future, the application models can be tied to data on student progress to help identify which kinds of support have been most successful for different groups.

Conclusion

In summary, UMUC and Capella University currently leverage data analytics to support learners’ success and outcomes by providing relevant and engaging resources and support. Both institutions also continue to identify and evaluate new ways to incorporate data analytics into initiatives designed to support these outcomes.