Short answer

When designing or implementing advising technologies, prioritize user-friendliness and provide comprehensive support that acknowledges and addresses varying levels of advisor experience and technological comfort.

Field: Human Factors
Source: KU ScholarWorks (The University of Kansas) (2018)
Method: Comparative Case Study
Evidence: Moderate effect

The successful integration of academic analytics tools into advising practices is significantly influenced by the flexibility and technological comfort of advisors. This human factors research insight is drawn from a 2018 study published in KU ScholarWorks (The University of Kansas). Using Comparative case study, researchers explored how this design variable affects real-world outcomes. The key design takeaway: When designing or implementing advising technologies, prioritize user-friendliness and provide comprehensive support that acknowledges and addresses varying levels of advisor experience and technological comfort.

Study

Human FactorsHigh ImpactModerate effect

Technology Adoption in Advising: Experience and Flexibility Drive Success

The successful integration of academic analytics tools into advising practices is significantly influenced by the flexibility and technological comfort of advisors.

KU ScholarWorks (The University of Kansas) · 2018

Key Findings

01Strategic planning focused on student success metrics was a primary driver for implementing academic analytics systems.
02Advisors with less experience and greater flexibility in their approach and with technology were more successful in adapting to new tools.
03The implementation of new tools did not fundamentally alter existing advising approaches at the institutions studied.

Application

Design takeaway

How to apply

When introducing new software to a team, assess the team's current technological proficiency and provide tiered training and ongoing support to accommodate different learning curves.

Project actions

01When researching user adoption of a new tool, consider surveying users about their prior experience and comfort level with similar technologies.
02Observe how users interact with a new design and note any hesitations or workarounds that might indicate a need for further training or design adjustments.

Method & Evidence

AimWhat factors influence the successful implementation and adoption of academic analytics tools by academic advisors?

MethodComparative Case Study

ProcedureTwo public, 4-year, doctoral degree-granting institutions were studied to understand their implementation of an academic analytics system (EAB SSMS). The research examined the steps taken during implementation, the impact on advising work, and the perceived changes to existing advising philosophies.

ContextHigher Education - Academic Advising

Variables

IV["Advisor's flexibility and technological comfort","Implementation strategy of the academic analytics tool"]

DV["Success/effectiveness of tool adoption","Impact on advising work"]

CV["Type of institution","Specific academic analytics system used"]

Strengths & Limitations

Strengths

+Comparative approach allows for identification of differences and similarities in implementation.
+Focus on real-world implementation in academic institutions.

Limitations

The findings might not apply to all types of advising software or to institutions with very different advising structures or cultures.

Reliability & validity

The comparative case study method provides rich qualitative data, but the findings' generalizability may be limited. Reliability could be enhanced by using standardized observation protocols and multiple data sources (e.g., interviews, system logs).

Think critically

To what extent can technology truly transform a deeply ingrained professional philosophy, or does it primarily serve to enhance existing practices?

Design Principles

"User adaptability is a critical factor in the successful integration of new technologies within professional workflows."

As educational institutions increasingly adopt data-driven tools to support student success, understanding the human element of adoption is crucial. Designers and institutions must consider the varying levels of experience and adaptability among users to ensure effective implementation and maximize the benefits of these technologies.

What This Means for Your Design

When schools add new computer programs to help students, the people using them (advisors) need to be good with computers and willing to learn new things for it to work well. The programs usually help advisors do their job better but don't change how they advise students completely.

How to use in your project

1.Reference this study when discussing the human factors involved in the adoption of new technologies within a design project, particularly concerning user training and support strategies.

Add to My Project

Quick Cite

Paragraph starter

The implementation of new technological systems within professional environments, such as academic advising, is significantly influenced by the human factors of user adaptability and technological proficiency. Research indicates that advisors with greater flexibility and comfort with technology are more likely to successfully integrate new tools, suggesting that design and implementation strategies should account for varying user experiences and provide tailored support to ensure effective adoption and maximize the benefits of the technology.

Source

KU ScholarWorks (The University of Kansas)

Implementing Academic Analytics and the Impact to Academic Advising

journal · 2018

View source

Questions About This Research

What does the research say about technology adoption in advising: experience and flexibility drive success?: When designing or implementing advising technologies, prioritize user-friendliness and provide comprehensive support that acknowledges and addresses varying levels of advisor experience and technological comfort. Evidence: KU ScholarWorks (The University of Kansas) (2018).
Why does "Technology Adoption in Advising: Experience and Flexibility Drive Success" matter for design?: As educational institutions increasingly adopt data-driven tools to support student success, understanding the human element of adoption is crucial. Designers and institutions must consider the varying levels of experience and adaptability among users to ensure effective implementation and maximize the benefits of these technologies.
How can designers apply this research?: When designing or implementing advising technologies, prioritize user-friendliness and provide comprehensive support that acknowledges and addresses varying levels of advisor experience and technological comfort.
What were the main findings?: Strategic planning focused on student success metrics was a primary driver for implementing academic analytics systems.. Advisors with less experience and greater flexibility in their approach and with technology were more successful in adapting to new tools.. The implementation of new tools did not fundamentally alter existing advising approaches at the institutions studied.
What research method was used?: Comparative Case Study.
How strong is the evidence?: Evidence strength is rated Moderate effect, based on a 2018 journal from KU ScholarWorks (The University of Kansas).
What should I do differently in my next project?: When introducing new software to a team, assess the team's current technological proficiency and provide tiered training and ongoing support to accommodate different learning curves.
What are the limitations?: The study focused on specific institutions and a particular software system, potentially limiting generalizability to all higher education contexts and analytics platforms.