Technology Effectiveness in Teaching Statistics: Best-Evidence Meta-Analysis
DOLE Spotlight 'Women Who Author Boldly Submission
Why Technology Often Fails the Leaders Closest to Their Communities
Minority leaders are frequently asked to adopt standardized technologies and “best practices” that were not designed with their communities, cultural contexts, or ways of working in mind, yet they are still held fully accountable for outcomes.
In practice, similar tools produce very different results across institutions and organizations. Some initiatives support learning in meaningful ways, while others stall despite comparable resources.
What if the issue isn’t leadership capability, but how effectiveness is being defined and measured?
What If the Difference Is How Leaders Shape Learning, Not the Tools They Use?
Rather than asking which technologies work best, this research examines a more consequential question:
Under what conditions does technology actually support learning, especially in diverse, real-world contexts?
What This Research Examines
Drawing on a best-evidence synthesis of 32 experimental and quasi-experimental studies spanning two decades, this dissertation examines technology use in post-secondary statistics education with a focus on how learning experiences are shaped by those closest to instruction.
Instead of comparing tools, the analysis identifies patterns across studies that show how local decision-making, collaboration, instructional support, and sustained engagement influence whether technology contributes to learning at all.
Why This Work Matters for Minority Leaders
Much of the technology conversation assumes neutrality—that tools function the same way across settings if implemented correctly. This assumption often ignores the realities minority leaders navigate: constrained resources, diverse learners, and the need to adapt systems to fit people rather than the reverse.
The evidence challenges this assumption.
Across studies, technology produced modest gains overall, but stronger and more consistent outcomes when learning experiences were shaped by contextual knowledge, shared problem-solving, and ongoing support over time.
In other words, the leadership practices minority leaders often rely on to make systems work under constraint are the very practices the evidence most strongly supports.
What Readers Gain from the Full Dissertation
Accessing the full dissertation provides insight into:
why standardized technology initiatives yield uneven results across contexts
how locally informed design decisions shape learning outcomes
why collaboration, feedback, and sustained engagement matter more than platform features
what leaders should consider when evaluating technology beyond adoption metrics
Who This Is For
This work is intended for minority leaders, educators, organizational decision-makers, and practitioners who are responsible for making technology-supported learning work in complex, diverse environments.
About the Author
Dr. Tiamuh is a researcher and practitioner whose work focuses on how learning systems function across diverse institutional and community contexts. She examines how design, implementation, and local decision-making shape whether technology meaningfully supports learning.
Through rigorous synthesis and applied inquiry, she studies how leaders working in complex environments can adapt tools, structures, and strategies to fit real conditions—moving beyond surface-level adoption metrics toward sustained, context-grounded impact.
Evidence-to-Decision Brief
👉 Access the full dissertation to explore how evidence affirms the leadership practices in technology use that make learning possible across contexts.
ARTICLE ABSTRACT
ABSTRACT
Evidence about technology effectiveness in supporting post-secondary students’learning of introductory statistics concepts is inconclusive.
Lacking in current investigations are considerations of the synergies between technology, content, and pedagogy that influence learning outcomes in statistics education. The current study usedmeta-analytic procedures to address the gap between theory and practice related to the best evidence of effective instructional practices in technology-enhanced introductory statistics classrooms. A conceptual framework based on the ADDIE model, TPACK, and constructivism guided the investigation of substantive study characteristics related to instructional design.
