AI in Education: Can Students Still Learn Alone? : Nirvana Ghezaei
AI in Education: Can Students Still Learn Alone?
The Future of Independent Learning in the Age of AI
By Nirvana Ghezaei | June 2026
C an students still learn alone? Yulianti and Aras (2026) suggest that the answer is neither a simple "yes" nor "no," but rather "yes, with the right support." Their systematic review on AI and independent learning found that students can learn by themselves, but independent learning is strongest when coupled with appropriate structure, instructor feedback, AI support, or peer collaboration.
Introduction
Can students still learn independently in an age where artificial intelligence is becoming part of everyday education? As AI-powered tools become increasingly common in classrooms, educators are questioning whether these technologies promote independent learning or encourage dependence on artificial intelligence. If forced to summarize the research into a single sentence, one could say: students do not suddenly become incapable of learning when the teacher stops directing their activities, but some students will struggle if left to their own devices. Researchers such as Zimmerman (2002) and Knowles (1975) have long argued that independent learning develops through self-regulation, self-directed learning, learner agency, and metacognitive strategies. Supportive technology is becoming an important pillar in its own right. This research matters because schools are often asking students to work more independently than ever before, at the same time as they face digital distractions, artificially intelligent tools, and inconsistent work habits.
Biggest Take Away
The emerging consensus among researchers: pure independence is a myth. Yulianti and Aras (2026) concluded that AI can support better personalized instruction, increase student motivation, provide flexible access to learning, and encourage self-regulation. However, those benefits come with risks like AI overreliance, weak digital-literacy skills, privacy violations, and academic dishonesty.
Younis (2024) found that while generative AI tools can increase students' perceived autonomy and confidence in online learning, excessive dependence on these technologies may reduce genuine learner independence. Researchers found that heavy AI use was associated with students’ perceived autonomy in learning, but that dependence on the tools could lead to decreased autonomy.
Independence is stronger when connected to related skills like self-regulation. Historically, self-directed learning was defined as learning “that is done by oneself without direct supervision,” making it sound like a trait some students have and others do not. Recent literature leans away from viewing independence as a personality characteristic. A literature review on learner agency in undergraduate dental education (2024) concluded that self-regulated learning and self-directed learning prepare students to become active agents in lifelong learning. Knowles (1975) described self-directed learning as a process in which learners identify their learning needs, establish goals, locate resources, implement learning strategies, and evaluate outcomes.
Areas Of Debate
First, whether technology is a help or a hindrance. Clarke (2026) described AI tools as "guides, planners, and scaffolds" that help students become more independent learners and thinkers. However, Younis (2024) reported that some students viewed generative AI tools such as ChatGPT as "like magic," raising concerns that students may rely on AI instead of developing their own critical-thinking and problem-solving skills. Independence means little if technology allows students to outsource thinking and critical reflection. The disagreement is not whether students can learn alone, but whether they should learn alone.
Second, how researchers measure independent learning. Much of this literature still relies on self-report surveys of learners, which may say more about student confidence than their actual independent-learning skills. Additionally, Robinson and Persky (2020) argued that self-directed learning is strengthened when students receive guidance and feedback rather than being left completely on their own. Consequently, researchers continue to debate how independent peer learning truly is, with several studies suggesting that collaborative learning environments often produce stronger self-regulated learning than studying entirely alone. Therefore, it can be difficult to interpret how learners will perform outside of studies.
Questions for Future Research
Longitudinal data. The majority of the articles included literature reviews or were not longitudinal. Instead, they studied self-directed learning through a single intervention or survey. While that approach produces useful results, researchers know less about how independent-learning skills develop over the long term.
Confounding factors. Some studies included high school students and undergraduate learners together, making it difficult to tell if findings were specific to a certain age group or life stage. Other studies did not clearly differentiate between different types of learners (e.g., vocational students versus graduate students).
Context. There is still relatively more literature on independent learning in higher education or health professions than on K-12 learners or language learners. Countries other than the United States and China are also rarely discussed. Researchers need to compare how students learn alone versus with peers versus with AI across different outcomes. Right now, studies suggest the answer depends on the task, the learner’s skill level, and intensity of support.
Learning Theory
Knowles' (1975) Self-Directed Learning Theory explains that learners become more independent when they take responsibility for setting goals, selecting learning resources, and evaluating their own progress.
Zimmerman's (2002) Self-Regulated Learning Theory explains that learners monitor, evaluate, and adjust their learning strategies to achieve their goals.
Conclusion
Students can learn by themselves, but rarely effectively by themselves. As of 2026, the strongest evidence suggests it is possible to foster independent learning if educators balance independence with periodic feedback, good instruction, and judicious use of AI. Instead of asking whether students can learn alone, researchers and teachers should ask how much support students need. Yulianti and Aras (2026) also emphasized the need for more longitudinal studies examining AI's long-term influence on learner independence.
Ultimately, the question is not whether AI should replace independent learning, but how educators can use AI responsibly to strengthen students' ability to think critically and learn independently.
References
Clarke, B. (2026, January 3). AI in education 2026: From tools to proactive teammates. Beverly Clarke Consulting.
https://beverlyclarkeconsulting.co.uk/2026/01/03/ai-in-education-2026-from-tools-to-proactive-teammates/
Gupta, N., Ali, K., Jiang, D., Fink, T., & Du, X. (2024). Beyond autonomy: Unpacking self-regulated and self-directed learning through the lens of learner agency: A scoping review. BMC Medical Education, 24, 1519.
https://pmc.ncbi.nlm.nih.gov/articles/PMC11667877/
Robinson, J. D., & Persky, A. M. (2020). Developing self-directed learners. American Journal of Pharmaceutical Education, 84(3).
https://pmc.ncbi.nlm.nih.gov/articles/PMC7159015/
Younis, B. K. (2024). Examining students' self-regulation skills, confidence to learn online, and perception of satisfaction and usefulness of online classes in three suggested online learning environments that integrate ChatGPT. Online Learning, 28(2).
https://eric.ed.gov/?id=EJ1428226
Yulianti, L. D., & Aras, M. S. (2026). The impact of AI on students' independency in learning: A systematic review. Entinas: Journal of Education and Technology.
https://jutepe-joln.net/index.php/ENTINAS/article/view/1233
DEEcode
All rights reserved. All creative works published on DEEcode are original unless otherwise credited.
Comments
Post a Comment