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AI Adoption Among Teachers: Insights on Concerns, Support, Confidence, and Attitudes

Based on a study of 260 teachers in the Philippines, institutional support significantly improves attitudes toward AI adoption by increasing teacher confidence, while teacher concerns do not moderate these relationships, suggesting that structured support and professional development are key to effective AI integration.

Original authors: Vanessa B. Sibug, Maria Anna D. Cruz, Vicky P. Vital, Juvy C. Grume, Almer B. Gamboa, Emerson Q. Fernando, Lloyd D. Feliciano, Jordan L. Salenga, John Paul P. Miranda

Published 2026-05-04

📖 4 min read☕ Coffee break read

CC BY 4.0

Original authors: Vanessa B. Sibug, Maria Anna D. Cruz, Vicky P. Vital, Juvy C. Grume, Almer B. Gamboa, Emerson Q. Fernando, Lloyd D. Feliciano, Jordan L. Salenga, John Paul P. Miranda

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine a school as a giant, bustling kitchen where teachers are the chefs. For a long time, they've cooked with traditional tools. Now, a new, high-tech "Smart Oven" (Artificial Intelligence) has arrived to help them bake better, faster, and more personalized meals for their students. But before the chefs can use it, they need to know: Will they trust it? Will they feel confident using it? And will the kitchen manager (the school) help them?

This study, conducted by a team from Pampanga State University in the Philippines, looked at 260 teachers to understand how they feel about this new "Smart Oven." Here is what they found, explained simply:

The Main Ingredients

The researchers looked at four main things:

Institutional Support: How much the school helps (providing tools, training, and rules).
Teacher Confidence: How sure the teachers feel about using the tech.
Teacher Concerns: The worries teachers have (like "Is this safe?" or "Will I break it?").
Attitudes: Whether the teachers actually like the idea of using the AI.

The Big Discovery: The "Safety Net" Effect

The study found that Institutional Support is the most important ingredient. Think of it as a safety net or a training manual provided by the school.

What the data says: When schools gave teachers good resources, training, and clear guidelines, the teachers' confidence skyrocketed.
The Surprising Twist: The researchers thought that if a teacher was really worried (high "concerns"), the safety net wouldn't work as well. They thought the worries would block the help. But that didn't happen.
The Metaphor: Imagine a tightrope walker (the teacher). Even if they are scared of falling (concerns), if the safety net (school support) is strong and visible, they still feel brave enough to walk the rope. The worries didn't stop the support from working. The support was so strong that it drowned out the fear.

The Chain Reaction: Support → Confidence → Attitude

The study also looked at how these feelings connect. They found a clear chain reaction, like a line of dominoes falling:

The First Domino (Support): The school provides the tools and training.
The Second Domino (Confidence): This makes the teacher feel, "I can do this!"
The Third Domino (Attitude): Because they feel confident, they start to love the idea of using the AI.

The Key Finding: The school's support didn't make teachers like the AI directly. Instead, the support made them confident, and that confidence is what made them like the AI. If you take away the confidence, the support doesn't seem to matter as much for their attitude. It's like giving someone a fancy car (support); they won't love driving it until they actually learn how to drive it and feel safe behind the wheel (confidence).

What About the Worries?

The study checked if teachers' worries about privacy or technical glitches changed the outcome.

The Result: The worries were actually quite low to begin with. Even when they were present, they didn't stop the support from boosting confidence or change how teachers felt about the AI.
The Metaphor: It's like having a few small pebbles in your shoe. If the road is smooth and the shoes are well-made (strong support), you don't even notice the pebbles, and you keep walking happily.

The Bottom Line

The paper concludes that if schools want teachers to embrace AI, they shouldn't just try to "fix" the teachers' fears. Instead, they should focus on building the safety net.

What works: Providing structured training, mentoring, and reliable tools.
Why it works: These things build confidence.
The Result: Confident teachers naturally develop positive attitudes toward the new technology.

In short, the study suggests that confidence is the magic bridge. Schools build the bridge (support), teachers cross it (gain confidence), and on the other side, they find a positive attitude toward AI. The worries they had along the way didn't stop them from crossing.

1. Problem Statement

Despite the rapid integration of Artificial Intelligence (AI) in education, many teachers face barriers to adoption, including limited training, unreliable technology access, and ethical concerns (e.g., data privacy). While existing literature acknowledges the roles of institutional support and teacher confidence, there is a gap in understanding:

How these factors interact to shape teacher attitudes.
Whether teacher concerns act as a moderator that weakens the positive effects of institutional support.
Whether teacher confidence acts as a mediator explaining how institutional support translates into positive attitudes toward AI.

The study aims to address these gaps by testing a moderated mediation model grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT).

2. Methodology

Research Design: Quantitative study employing a cross-sectional survey design.
Participants: A sample of 260 teachers from Pampanga, Philippines, comprising:
- 52 Elementary educators
- 161 Secondary educators
- 47 College educators
- Demographics: >75% female, ~80% licensed professionals, ages 22–59, experience 1–36 years.
Instrument: A 35-item survey using a 5-point Likert scale (1 = Strongly Disagree to 5 = Strongly Agree) measuring four constructs:
1. Institutional Support (Facilitating Conditions)
2. Teacher Confidence (Self-Efficacy)
3. Teacher Concerns (Inhibitors)
4. Attitudes (Behavioral Intention)
Validity & Reliability: Content validity was established by two experts; reliability was confirmed with Cronbach's alpha ( $\alpha$ ) > 0.70 for all constructs.
Data Analysis Tools: Python libraries and Jupyter Notebook.
Statistical Techniques:
- Moderated Multiple Regression (MMR): To test if "Concerns" moderate the relationship between "Support" and both "Confidence" and "Attitudes."
- Mediation Analysis: Using the Baron and Kenny method and the Sobel test to determine if "Confidence" mediates the relationship between "Support" and "Attitudes."

3. Key Results

The study yielded three primary statistical findings:

A. Descriptive Statistics

Attitudes: Highly positive ( $M=4.92$ ). Teachers strongly agree on AI's benefits for learning and engagement.
Confidence: High overall ( $M=4.72$ ), though confidence in handling technical issues was slightly lower.
Concerns: Low ( $M=2.14$ ), indicating minimal apprehension regarding privacy or overreliance.
Institutional Support: Generally strong ( $M=4.32$ ), particularly regarding device access and ethical guidelines, though internet infrastructure support was rated lower.

B. Moderated Regression Analysis (MMR)

Support $\rightarrow$ Confidence: Institutional support significantly predicted teacher confidence ( $\beta = 0.537, p < 0.001$ ).
Moderation Effect: Teacher concerns did NOT significantly moderate the relationship between support and confidence ( $\beta = 0.021, p = 0.661$ $β = 0.021, p = 0.661$ ) nor between support and attitudes.
- Implication: Institutional resources and training outweigh individual fears in building confidence. Even with concerns, strong support leads to high confidence.
Model Fit: The model explained 47.6% of the variance in confidence ( $R^2 = 0.476$ ).

C. Mediation Analysis

Direct Effect: Institutional support did not have a significant direct effect on attitudes ( $\beta = 0.128, p = 0.106$ ) when confidence was controlled.
Indirect Effect: Institutional support significantly predicted confidence ( $\beta = 0.58$ ), which in turn strongly predicted attitudes ( $\beta = 0.85$ ).
Full Mediation: The Sobel test confirmed a significant indirect effect ( $a \times b = 0.4961, z = 12.63, p < .001$ $a \times b = 0.4961, z = 12.63, p < .001$ ). When confidence was included, the direct path from support to attitudes became non-significant.
- Implication: Institutional support improves attitudes only by first increasing teacher confidence.

4. Key Contributions

Clarification of Mechanisms: The study moves beyond simple correlation to establish a full mediation model. It proves that institutional support does not directly change teacher attitudes; rather, it builds the self-efficacy (confidence) required to form positive attitudes.
Role of Concerns: Contrary to the hypothesis that concerns would hinder adoption, the study found that concerns are not a significant barrier when institutional support is robust. This suggests that structural support can neutralize psychological inhibitors.
Extension of UTAUT: The research extends the Unified Theory of Acceptance and Use of Technology by empirically validating the specific pathway where "Facilitating Conditions" (Support) $\rightarrow$ "Self-Efficacy" (Confidence) $\rightarrow$ "Attitude."

5. Significance and Recommendations

Strategic Focus for Institutions: Schools should shift focus from merely providing hardware to building teacher confidence. Support systems must include structured professional development, mentoring, and AI literacy integration in teacher education.
Policy Implications: Resistance to AI is often a symptom of systemic support gaps rather than individual reluctance. Policymakers must ensure continuous technical assistance and infrastructure reliability.
Future Readiness: To achieve sustainable AI adoption, educational institutions must prioritize psychological readiness (confidence) alongside technical readiness. The study suggests that once confidence is established through support, teachers are naturally inclined toward positive AI adoption regardless of their initial concerns.