Bringing It All Together
- petersonkaitlinm
- Sep 22, 2024
- 10 min read
Challenges Identified
During Spring 2024, I conducted a campus-wide needs assessment with 17 individual academic advising units at Michigan State University. The needs assessment was done through facilitated feedback sessions in which units shared challenges they were experiencing and opportunities for additional support. After initial brainstorming, each group was asked to narrow these ideas down to their top 3.
After collecting the top 3 needs from each unit, I analyzed the data to identify patterns and consistent requests. In doing so, I discovered that there was a common request for knowing how to pull data from advising systems, specifically Campus Solutions Student Information System (SIS), to identify at risk students and create interventions to improve student persistence. Academic advisors felt that the systems were confusing and there wasn't a tutorial or clear guidance on how to effectively use the queries in SIS. The data acquired from SIS would help identify students that are missing major requirements, students with GPAs below a certain threshold, and students who have not yet attended an advising appointment. Without understanding how to use queries in SIS, advisors felt they were unable to be proactive in supporting their students and missing opportunities to assist at-risk students.
To address this common concern, I will create a virtual asynchronous course for academic advisors that will guide them through using and manipulating queries in the Student Information System, steps for analyzing data, and methods for applying this information to strategies to support their student population. This training will help advisors at MSU with locating, pulling, and analyzing data from SIS for their unique student groups. The program is intended for undergraduate academic advisors at MSU at all levels of experience, with at least some experience SIS to view student information. Advisors have limited time to spend on professional development, and a flexible training program is needed so that advisors can schedule their training on their own time. Being able to directly apply what they've learned is also beneficial, with advisors most often attending training that are directly applicable to their work.
Learning Objectives
By the end of the course, academic advisors will be able to review student data from queries within the Student Information System and locate specific information related to academic standing, unmet degree requirements, number of advising appointments. Academic advisors will also be able to identify at-risk students within the advisor's assigned student population using academic standing and degree completion information. Finally, academic advisors will develop proactive outreach strategies from the data acquired that aims to improve student success.
The Learners
In designing this asynchronous course, I am focusing on undergraduate academic advisors at Michigan State University with a range of experience levels. These advisors have foundational knowledge in using the Student Information System (SIS) but may be unfamiliar with building or using queries within this system. Since no prior experience with queries is required, the program includes beginner-friendly modules that become incrementally more challenging to slowly build the advisor’s confidence with using queries.
Advisors have limited time in their day, often spending most of their day meeting with students, to participate in professional development. Given these constraints, this program is designed to be self-paced and flexible, allowing advisors to engage in short, manageable modules when they can. Content is chunked into easily digestible units, each taking no more than 15 minutes to complete. To further support advisors, the program includes downloadable job aids and practice exercises that can be revisited as needed, as well as progress tracking within the virtual course so that they can pick up where they left off.
Personal Philosophy of Learning
Considering my personal philosophy on learning, I closely align myself with self-directed learning as it offers flexibility and more control over a learning experience. Advisors will be able to control when they will engage with course materials due to the self-paced nature of the course, how frequently they review content (play-back videos, revisit job aids), and activities will give the advisor opportunities to apply what they've learned directly to their student population and future initiatives. Adult learners often seek education for professional advancement, career change, or skill development, which provides clear motivation for completing the activity, and I have found that workshops that garner most interest are those that directly impact advisors' work with students. Learning is also a construction of meaning from experiences, and I believe learners connect experiences with existing beliefs to create new meaning. For example, advisors are frequently discussing student progress and time to degree and are aware that proactive measures are needed for at-risk students.
By learning how to pull queries and create data-driven strategies, advisors can enhance their understanding of students that may struggle with persisting. Finally, I find that retention of new information is improved when the learning experience incorporates reflection on what was learned. This reflective process, as shared by Curtis (2021) in his article on Liberatory Education, “this reflective process, known as conscientization, enables deeper awareness and social responsibility.” The video tutorials and activities incorporated throughout will ask advisors to manipulate query filters and analyze data for their student populations, then reflect on different initiatives that could be created from this data to support student success.
Theoretical Framework
The theoretical framework I am applying to this online asynchronous course is the Situated Learning Theory. Situated learning posits that knowledge and skills are most effectively learned within real-world contexts, such as an auto mechanic apprenticeship, which requires considerable hands-on experience while guided by experts in the field. Hansman (2001) discussed this as cognitive apprenticeship, specifically approximating, in which learners try out an activity while describing their thoughts about what they are doing during the activity, then reflecting on what they did compared to an expert. Within Situated Learning Theory, situated cognition states that learning is contextual, influenced by activities, environment, and culture. Situated learning uses storytelling to store and access information based on the situation, reflecting during and after a learning experience, activities mimic real-world experiences, peers work together to solve problems, experts and facilitators provide scaffolding to learners, multiple opportunities for practice, learners describe their thinking process, and support from technology for virtual replication of different contexts.
Applying Theory Towards the Learners
Incorporating principles of Situated Learning Theory to academic advisors, the program emphasizes learning in the context of the advisor’s area of focus and student population, allowing advisors to directly apply what they learned to their day-to-day tasks. This aligns with Merriam and Bierema’s (2013, p. 118) notion that situated learning focuses on learning in practice within a specific context, which includes the environment, tools, social interactions, and cultural influences. As advisors are immersed in an environment and culture of student success and support, they are motivated by programs that can apply skills directly to their work with undergraduates. Because situated learning is context-based and emphasizes real-world scenarios, and our learners come from a range of cultural, social, and environmental contexts, it is vital that this course be accessible and designed with various modes of interaction. For example, video walk-throughs of the query-building process, a mock query addressing a student population needing points of contact, and integrated opportunities for peer connection, such as discussion boards or assignments designed for review with a supervisor or colleague. Thus, video tutorials in the course will include visuals, audio, and closed captioning to ensure accessibility. Straub in Roundup Research further noted that “dual streams of information (visual and auditory) can help in understanding material better” (2024). Downloads will also be provided in Word Document format with appropriate headings.
Introduction to Facilitation Methods
The facilitation used in this course is grounded in three key educational methods: Constructivist Learning, Self-Directed Learning, and Kolb’s Cycle of Learning. These methods incorporate real-world application, hands-on experiences, reflection, autonomy, and connecting prior knowledge with new experiences, all of which are aligned with the course’s learning objectives. These concepts directly align with adult learning, which according to Ajayi (2019), "is premised on five key tenets: self-concept; experience; readiness to learn; orientation to learn; and motivation." Advisors will engage in three practice modules that become progressively more complex. First, advisors will receive the most guidance and conduct a simpler data request by only identifying students that have not yet met with an academic advisor. Building off this foundation, the second module asks advisors to find students within their program who are on academic probation with a cumulative GPA below 2.00. A final and more complex scenario requests advisors to locate students in their major or program who are scheduled to graduate next semester but have not met all of their degree requirements. These activities progressively increase in complexity, allowing advisors to gain confidence and deepen their understanding. Following Daley (2002) "learning activities should cause learners to gain access to their experiences, knowledge and beliefs,” which helps advisors to critically address challenges impacting their students. Advisors will also complete a pre- and post-course surveys to gauge their understanding of SIS queries, intended use of data in their advising practice, and to provide feedback for future course enhancements.
Facilitation Approach: Constructivist Learning
Constructivist learning is an ideal approach for both facilitation and practice in this course because it emphasizes real-world application through case-based examples. According to Perin (2011), contextualization helps learners to apply skills in meaningful ways and to transfer information across a variety settings. Advisors will engage in problem-solving as they navigate the system, troubleshooting any issues that arise if the data doesn’t appear as expected. Additionally, advisors will be encouraged to collaborate and discuss their findings with their supervisor and team, specifically when designing interventions and outreach campaigns. Learning, according to Hansman (2001), is inherently social, influenced by people, tools, and activities within each context. This collaborative component integrates social learning and peer-to-peer facilitation in which advisors can share insights, discuss challenges, and reflect on their learning to deepen their understanding with a partner.
The course structure uses facilitation through scaffolding to support the learner’ progression, starting with step-by-step video instructions on how to navigate this course. This is important because “adults may be self-directed in some situations but at other times prefer or need direction from others” (Kerka, 2002). This course aims to strike a balance in the amount of guidance provided, with more being present at the beginning and gradually decreasing. The first module introduces advisors to locating queries within the Reporting Center of the Student Information System (SIS) and familiarizes them with types of reports that are relevant to advisors. For the first practice activity, advisors will receive detailed instructions to help them successfully pull data. As the course progresses, the level of guidance is decreased and the activities increase in complexity, allowing the advisor to become more independent in using queries. MacKeracher (2004) emphasized that facilitators should provide scaffolding early in the learning process and slowly dismantle it as learning progresses, which gives the learner opportunity for self-directed problem solving. The course also uses reflection, asking advisors to consider how they would apply this data to a student success initiative. Advisors reflect on strategies on how they can use this data to create interventions for probation students, how to create an outreach plan for students in their program that are missing degree requirements, and how to create a strategy to engage students that have not yet met with an advisor. In frequently modeling reflective practices throughout the course, I as the facilitator aim to help learners develop skills to critically think through problems and take control of their own learning.
Facilitation Approach: Self-Directed Learning
The structure of this course itself is designed to support Self-Directed Learning. As stated by Merriam and Bierema (2013), “The role of educators in self-directed learning is to act as facilitators, or guides as opposed to content experts.” This course is an online, asynchronous format, providing advisors with flexibility to complete it at their own pace and on their own schedule. Osborne and Schwartz’s (2016) article emphasized the advantages of SDL, specifically practice experience, skills development, and continuous learning. Self-Directed Learning (SDL) is a key element in this course, allowing learners to take control of and direct their learning experience. The course is optional, meaning advisors can choose to participate based on their interest in learning how to pull and analyze data that is relevant to their department or college. Learners are also given flexibility to select the specific student population they wish to focus on, and they have the autonomy to design interventions and initiatives based on the data they gather. In keeping with SDL principles, advisors are encouraged to set personal goals for this course, deciding what they hope to achieve and what strategies or resources they will use to reach those goals. Successful SDL, as noted by Lin (2024), involves identifying areas for improvement and adjusting strategies to enhance outcomes. Facilitation plays an important role in self-directed learning by providing structured guidance to help advisors navigate new information while also encouraging autonomous problem-solving.
Facilitation Approach: Kolb’s Cycle of Learning
Kolb’s cycle of learning suggests that learning is rooted in past and new experiences but remains an internal process (MacKeracher, 2004, p. 203). In considering the four stages of Kolb’s Cycle, Concrete Experiences provide hands-on learning opportunities where advisors visually engage with query processes after receiving guidance from video tutorials. For example, using filters to narrow data and examine sample data requests. Reflective Observation, in which the learner “reflects on this experience from different points of view and gives it meaning” (MacKeracher, 2004, p. 57), is done by considering how query results could inform outreach and interventions for certain student populations. Abstract Conceptualizing occurs as advisors are introduced to new concepts through video tutorials and then asked to apply this new knowledge to their own student populations, exploring potential initiatives that would support these groups. Finally, Active Experimentation allows advisors to practice using query builders within SIS through structured scenarios, encouraging experimentation with datasets to deepen their skills in using queries.
References
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