Enterprise AI Analysis
Using technology for questioning evidence in pre-service teacher education
This article describes a redesign of a pre-service teacher education program focusing on using technology to support pre-service mathematics teachers in critically evaluating evidence. Based on a design-based research approach and interviews with pre-service teachers, the study concludes that technology can effectively aid evidence-use, especially in the 'questioning' phase of Engeström's expansive learning cycle. It also proposes future redesigns incorporating generative AI to further enhance evidence-based practices.
Executive Impact & Key Findings
Leveraging technology, this study demonstrates a pathway to enhance critical evidence-use in teacher education, fostering adaptability and informed decision-making among pre-service teachers.
0
Key Themes Identified
0
Program Iterations
0
Teacher Interviews Conducted
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Explores how technology is used in teacher preparation, from basic literacy to pedagogical applications, and the emerging role of AI.
Focuses on the definition and mechanisms of evidence-use in education, emphasizing critical engagement and the expansive learning cycle.
Details the methodology and iterative design process of the pre-service teacher education program, incorporating evidence-use and technology.
5
Pre-service teachers interviewed providing qualitative data.
Expansive Learning Cycle in Teacher Education
The redesigned program maps its activities to Engeström's expansive learning cycle, highlighting the crucial role of technology in key phases like questioning and analysis.
Questioning (Technology Supported)
→
Analysis (Search Skills, Literature)
→
Modeling new solution (Empirical Plan)
→
Examining & testing (Execution of Plans)
→
Implementing new model (Data Analysis)
→
Reflecting on process (Interviews, Feedback)
→
Consolidating & generalizing (Future Practice)
| Traditional Approach | Redesigned Program (RiTE Project) |
|---|---|
|
|
Pre-service Teachers' Perspective on Evidence & Technology
Interviews revealed three key themes regarding how pre-service teachers perceive and use technology for evidence. They value multiple sources but challenge unreliable ones, prefer 'hard' evidence, and use technology instrumentally for data collection.
Impact: The program successfully fostered critical assessment skills, enabling teachers to navigate conflicting digital information and integrate evidence into their practice. However, time constraints remain a practical challenge for extensive personal research.
Calculate Your Potential AI-Driven ROI
Estimate the efficiency gains and cost savings your organization could achieve by implementing AI solutions based on insights from this research.
Estimated Annual Savings
Annual Hours Reclaimed
Implementation Roadmap
A phased approach to integrating AI-powered evidence-based practices in your educational or training programs.
Identify Research Question & Self-Evaluation
Defining the problem and assessing existing program elements against the goal of critical evidence-use.
Program Redesign & Expert Review
Developing new elements for technology-supported questioning and analysis, reviewed by the wider project team.
First Cohort Implementation (2020-21)
The redesigned program is used with 23 secondary mathematics pre-service teachers, with tutors guiding technology integration.
In-depth Interviews (Cohort 1) & Analysis
Collecting qualitative feedback from 3 pre-service teachers focused on technology and evidence-use mechanisms.
Program Revisions for Next Cohort
Refining the program based on initial feedback and insights for the subsequent academic year.
Second Cohort Implementation (2021-22)
The revised program is implemented with 21 pre-service teachers, further testing the refined design.
Further Interviews (Cohort 2) & Analysis
Collecting additional qualitative data from 2 pre-service teachers to deepen understanding of technology's role.
Generative AI Proof-of-Concept
Investigating the potential of tools like NotebookLM to provide interactive, Socratic dialogue for critical research evaluation.
Ready to Revolutionize Your Educational Programs with AI?
Our experts are ready to help you design and implement cutting-edge AI strategies for teacher education, curriculum development, and evidence-informed practice.
Ready to Get Started?
Book Your Free Consultation.
Let's Discuss Your AI Strategy!
Lets Discuss Your Needs
Select a Date
Sun
Mon
Tue
Wed
Thu
Fri
Sat