Why Technology Alone Can’t Transform Education

1. Technology alone cannot transform education

Schools are complex institutions negotiated by a diverse set of stakeholders: teachers, students, families, communities, school boards, trustees, vendors, state and federal governments, and others.

Complex ecosystems. Education systems are intricate webs of stakeholders, each with their own goals and priorities. This complexity makes it difficult for any single technological innovation to create sweeping changes. Schools serve multiple purposes beyond just academic instruction, including socialization, providing meals, and supporting working parents.

Resistance to change. The conservative nature of educational institutions often leads to new technologies being adapted to fit existing practices rather than fundamentally altering them. This "domestication" of technology means that even promising innovations may have limited impact when introduced into real-world educational settings.

Reasons for resistance:

• Entrenched practices and beliefs
• Limited resources for implementation
• Concerns about equity and access
• Skepticism from educators and parents

2. Three genres of learning at scale: Instructor-guided, algorithm-guided, and peer-guided

If we can situate a new technology in its history, we can make predictions about how that new technology will function when integrated into the complex ecology of schools.

Historical context matters. By understanding the lineage of educational technologies, we can better predict their potential impact and limitations. Each genre of learning at scale has its own strengths and weaknesses, which become apparent when examined through a historical lens.

Comparative analysis. Instructor-guided systems like MOOCs rely on traditional lecture-based pedagogy, while algorithm-guided systems like adaptive tutors use data to personalize learning paths. Peer-guided systems, exemplified by platforms like Scratch, emphasize collaboration and creativity. Each approach has found success in specific niches:

• Instructor-guided: Effective for motivated adult learners in professional fields
• Algorithm-guided: Shows promise in subjects like math and early reading
• Peer-guided: Fosters creativity and engagement, especially in informal learning contexts

3. The curse of the familiar: New technologies often reinforce existing practices

Technologies that look like typical elements in schools—like the practice problems on Khan Academy—scale much more easily than things that look very different from anything that has come before, like the open-ended programming environment on Scratch.

Familiarity breeds adoption. Educational technologies that closely resemble traditional teaching methods are more likely to be widely adopted. However, this familiarity often means that these tools do little to fundamentally change educational practices.

Innovation vs. integration. Truly innovative approaches that diverge significantly from established norms face greater resistance in schools. This creates a dilemma for edtech developers:

Easy adoption path:

• Digitize existing practices (e.g., online worksheets)
• Minimal disruption to current teaching methods
• Limited potential for transformative change

Challenging innovation path:

• Introduce novel learning experiences
• Requires significant changes in teaching and assessment
• Higher potential for meaningful impact, but harder to implement at scale

4. The edtech Matthew effect: Technology tends to benefit the already advantaged

New resources—even free, online resources—are more likely to benefit already affluent learners with access to networked technology and access to networks of people who know how to take advantage of free online resources.

Widening gaps. Despite hopes that technology would democratize education, research consistently shows that educational technologies often exacerbate existing inequalities. This "Matthew effect" in edtech means that those with more resources and prior educational advantages tend to benefit more from new tools and platforms.

Multifaceted barriers. The digital divide is not just about access to devices or internet connections. Social and cultural factors play a significant role in determining who benefits from educational technologies:

Technical barriers:

• Lack of reliable internet access
• Outdated devices or software

Social and cultural barriers:

• Limited familiarity with technology
• Lack of support networks for troubleshooting
• Cultural mismatch between tech design and user needs

Educational barriers:

• Varying levels of digital literacy
• Differing expectations for technology use in schools

5. The trap of routine assessment: Autograders limit the scope of what can be evaluated

Computers can only assess what computers themselves can do, so that's what we teach students. But in our economies and labor markets, we increasingly do not need people to do what computers are already good at.

Misaligned incentives. The limitations of automated assessment tools create a paradox in education technology. Autograders excel at evaluating routine tasks, precisely the kind of work that is increasingly automated in the modern economy. This mismatch can lead to a focus on teaching and assessing skills that may be less relevant in the future job market.

Creativity vs. computation. The challenge lies in developing technologies that can assess more complex, open-ended forms of thinking and problem-solving. Current limitations:

Easily assessed by computers:

• Multiple-choice questions
• Basic mathematical calculations
• Simple programming tasks

Difficult to assess automatically:

• Critical thinking and analysis
• Creative writing and argumentation
• Complex problem-solving
• Collaborative skills

6. The toxic power of data and experiments: Balancing research benefits with privacy risks

The toxic power of data and experiments highlights that even if questions about edtech's possibilities and potential are technical in nature, the questions of what we should do with technology are irreducibly political.

Ethical considerations. The vast amounts of data generated by educational technologies offer unprecedented opportunities for research and personalization. However, this data collection also raises serious concerns about student privacy, consent, and the potential misuse of information.

Balancing act. Educators and policymakers must navigate the tension between leveraging data for improvement and protecting student rights. Key considerations:

Benefits of educational data:

• Personalized learning experiences
• Early identification of struggling students
• Evidence-based policy decisions

Risks and challenges:

• Data breaches and unauthorized access
• Algorithmic bias in decision-making
• Long-term consequences of digital profiles
• Erosion of student autonomy and privacy

7. Tinkering towards improvement: Incremental changes over dramatic transformations

If the energy and excitement generated by new technologies could be applied not just to technology, but to technology and system change combined, that would provide the best possible chance for the field of learning at scale to meaningfully improve how people learn in schools and beyond.

Realistic expectations. Rather than expecting revolutionary changes, a more productive approach to educational technology involves making incremental improvements over time. This "tinkering" mindset acknowledges the complexity of educational systems and the need for sustained, multifaceted efforts to create meaningful change.

Holistic approach. Successful implementation of educational technologies requires attention to various interconnected factors:

Technology design:

• User-friendly interfaces
• Alignment with pedagogical goals
• Flexibility for different contexts

Professional development:

• Training for educators on effective integration
• Ongoing support and troubleshooting

Systemic changes:

• Curriculum alignment
• Assessment practices
• School schedules and structures

Community engagement:

• Involving stakeholders in decision-making
• Addressing concerns about equity and access

By focusing on gradual improvements and considering the broader educational ecosystem, we can work towards realizing the potential of technology to enhance learning while avoiding the pitfalls of overhyped "disruptive" solutions.

Last updated: October 12, 2024