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Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges
Open accessAbstract
Artificial intelligence (AI) is changing how we teach and learn, generating excitement and concern about its potential to transform education. To contribute to the debate, this systematic literature review examines current research trends (publication year, country of study, publication journal, education level, education field, and AI type), as well as the benefits and challenges of integrating AI into education. This review analyzed 155 peer-reviewed empirical studies published between 2015 and 2025. The review reveals a significant increase in research activity since 2022, reflecting the impact of generative AI tools, such as ChatGPT. Studies highlight a range of benefits, including enhanced learning outcomes, personalized instruction, and increased student motivation. However, there are challenges to overcome, such as students’ ethical use of AI, teachers’ resistance to using AI systems, and the digital dependency these systems can generate. These findings show AI’s potential to enhance education; however, its success depends on careful implementation and collaboration among educators, researchers, and policymakers to ensure meaningful and equitable outcomes.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This systematic review synthesizes 155 peer-reviewed empirical studies on AI in education, reporting a sharp rise in research since 2022 and especially 2023, alongside benefits such as enhanced learning outcomes, personalized instruction, and motivation. It also identifies persistent challenges including ethical concerns, teacher resistance, and digital dependency, concluding that AI’s success depends on careful, equitable implementation.
Key findings
- Research activity increased markedly: publication counts rose from 2 studies in 2015 to 35 in 2023 and 54 in 2024, with the paper linking the spike to generative AI tools such as ChatGPT.
- Most studies focused on higher education (97 studies), followed by secondary education (26), primary education (20), and teachers (12); language learning was the most represented education field (40 studies), followed by ICT (25) and science education (22).
- Benefits were grouped into 22 types across cognitive, personal, social, and teacher categories; AI was predominantly associated with cognitive and personal gains, especially enhanced learning outcomes, personalized instruction, and increased student motivation.
- Challenges were grouped into 16 types; the most frequently reported were ethical concerns (23 studies, 14.8%), teacher resistance (19, 12.3%), digital dependence (17, 11.0%), technical difficulties (10, 6.5%), and increased anxiety (9, 5.8%).
- Studies were conducted in 35 countries, with Asian nations—particularly China and Taiwan—and the United States dominating; Latin America and Africa were relatively absent. The reviewed studies appeared across 37 indexed journals, with *Computers & Education* most prominent.
Methods
- The review followed PRISMA and Kitchenham and Charters’ three-step process: planning, conducting, and reporting. Searches were run in Web of Science, Scopus, and Taylor & Francis using a defined AI/education/empirical-study search string, completed on 1 July 2025, yielding 3,406 potential studies; backward citation searching added 435.
- After removing 1,838 duplicates, 2,003 studies were screened by title, abstract, and keywords; 1,432 were excluded, 571 were assessed against inclusion/exclusion criteria, and 155 studies remained for final analysis.
- Data extraction covered title, authors, year, country, journal, education level, education field, AI type, benefits, and challenges. Thematic analysis used inductive coding in Microsoft Excel, with independent coding by two authors and disagreements resolved by the first author; Cohen’s Kappa was 0.89. Education levels and fields were standardized using ISCED.
Limitations
- The paper states that grey literature such as conference papers, dissertations, and policy reports was excluded, potentially omitting emerging or context-specific insights; it also states that it does not deeply explore how AI applications align with specific pedagogical models or teaching strategies, nor does it thoroughly examine long-term consequences such as changes in teacher roles, student autonomy, or institutional policies.
- The paper states that it did not apply a formal framework to assess certainty of evidence; confidence varies by theme, with cognitive and motivational benefits showing moderate to high confidence, while digital overdependence and ethical risks showed lower confidence due to less consistent reporting.
- Evident from the text: the abstract and methods report 155 studies published between 2015 and 2025, while the conclusion reports 132 empirical studies published between 2015 and 2024, an inconsistency in the reported sample size and date range.
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49 Own result · 35 Not checked yet · 29 Own interpretation · 17 Own method · 15 No basis given
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In the paper
“This analysis reveals a marked increase in research in 2023.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.1. Publication Year
boosted- Asserted: passes — The authors put it forward as true.
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In the paper
“Only one study included students from postgraduate programs (i.e., Master's or Doctoral programs); therefore, we included it in the higher education category.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.4. Education Level
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“Following closely, Interactive Learning Environments and Education and Information Technologies also stand out as prominent publication venues.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.3. Publication Journal
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In the paper
“Most studies examined short-term interventions; however, the growing use of AI in diverse educational contexts suggests the need for further research that explores its long-term integration.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.1. Publication Year
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In the paper
“Asian nations, particularly China and Taiwan, along with the United States, dominate the field.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.2. Country of the Study
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In the paper
“The review reveals a significant increase in research activity since 2022, reflecting the impact of generative AI tools, such as ChatGPT.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > Abstract
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In the paper
“The reviewed studies were published across 37 different indexed journals, indicating a broad and diverse interest in AI in education.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.3. Publication Journal
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In the paper
“Computers & Education emerged as the most prominent journal, highlighting its established role as a leading platform for empirical and theoretical contributions in the field of technology-enhanced learning.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.3. Publication Journal
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In the paper
“Most studies focused on higher education.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.4. Education Level
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In the paper
“This process allowed us to identify 16 different types of challenges.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
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In the paper
“Social benefits such as improved communication and collaboration are less frequently documented.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
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In the paper
“From the teacher's perspective, AI is most associated with task optimization, professional development, and time reduction.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
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In the paper
“This process allowed us to identify 22 different types of benefits.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
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In the paper
“Research focusing on AI-supported professional development, pedagogical decision-making, and classroom orchestration remains scarce and suggests greater attention [52].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.5. Education Field
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- Rests on an assumption: Educators play a central role in mediating the implementation of AI tools.
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In the paper
“In contrast, fields such as social sciences, services, and humanities (excluding language learning) remain underrepresented.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.5. Education Field
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In the paper
“Notably, 2.6% of studies lacked sufficient details to classify AI type, highlighting gaps in reporting standards.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.6. Type of AI
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In the paper
“The results reveal that AI in education is predominantly associated with cognitive and personal benefits, particularly enhancing learning gains and student motivation.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
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In the paper
“Despite the growing discourse on the potential of AI to support teacher professional development through intelligent tutoring systems, AI-driven feedback, and adaptive teaching simulations, empirical research on this topic remains scarce [14,52].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.4. Education Level
What the sources say
- Not checked yetcites [14] Sperling, 2024, In Search of Artificial Intelligence (AI) Literacy in Teacher Education: A Scoping Review, Comput. Educ. Open source
- Not checked yetcites [52] Ma, 2024, The Factors Influencing Teacher Education Students’ Willingness to Adopt Artificial Intelligence Technology for Information-Based Teaching, Asia Pacific J. Educ. source
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In the paper
“However, affective outcomes like reduced cognitive anxiety and enhanced creativity are comparatively underreported, indicating that these areas remain underexplored in current implementations.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
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In the paper
“The education field itself, including teacher training and pedagogy, also showed limited representation.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.5. Education Field
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In the paper
“Similarly, in physical education, culinary studies, and creative disciplines, AI has been explored in a limited capacity, despite its potential to augment experiential and multimodal learning [37].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.5. Education Field
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In the paper
“| | Increased cognitive load | Excessive information and multitasking can overwhelm students. | 6 | 3.9 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“with notable leadership from the journal Computers & Education.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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“In contrast, challenges related to digital overdependence or ethical risks appeared less consistently and with more variability in interpretation, indicating lower confidence.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 5. Limitations of the Study and Future Work
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In the paper
“Higher education emerges as the most studied level”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“| | Increased anxiety | Constant feedback and assessments can create stress and pressure. | 9 | 5.8 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“language learning, ICT, and science education stand out as the predominant content areas.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“In terms of benefits, AI is primarily associated with cognitive and personal gains.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“issues related to digital literacy”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“This systematic literature review examined 132 empirical studies published between 2015 and 2024 to identify the prevailing trends, benefits, and challenges of integrating AI in educational environments.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“| Personal challenges | Creativity barriers Autonomy limitations | Standardized AI-generated content may restrain originality. AI reliance might discourage independent learning strategies. | 9 6 | 5.8 3.9 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“| | Motivation issues | AI-driven learning may reduce intrinsic motivation if overused. | 5 | 3.2 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“| Social challenges | Reduced human interaction Communication barriers | AI-driven learning may limit peer collaboration and teacher-student engagement. Overuse of AI-based communication tools may affect interpersonal skills. | 8 3 | 5.2 1.9 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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“fosters autonomy.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“Challenges identified include ethical concerns”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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“improves motivation”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“most studies have been conducted in Asia, particularly in China, Taiwan, and Turkey”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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“| Teacher challenges | Low digital literacy | Limited AI proficiency among educators may reduce its effectiveness. | 9 | 5.8 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“| | Ethical concerns | AI raises ethical concerns about data privacy, algorithmic bias, decision transparency, and student surveillance risks. | 23 | 14.8 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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“| | High costs | AI implementation requires substantial investment in technology, training, and maintenance. | 8 | 5.2 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“potential over-dependence on AI”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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“| | Technical difficulties | Software glitches, connectivity issues, and integration challenges can disrupt learning. | 10 | 6.5 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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In the paper
“| | Legal aspects | intellectual property, accountability, and regulatory | 5 | 3.2 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| | Student's poor digital literacy | AI challenges students with low digital literacy, creating accessibility barriers and widening the knowledge gap. | 3 | 1.9 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“It enhances learning outcomes”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“social benefits, such as collaboration and cultural awareness, along with teachercentered advantages, are less emphasized”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| Cognitive challenges | Learning gains reduction | AI may hinder deep learning if misused or poorly designed. | 8 | 5.2 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“social benefits, such as collaboration and cultural awareness, along with teachercentered advantages, are less emphasized”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Moreover, the affective dimension of learning, such as reducing cognitive anxiety and promoting creativity, remains underexplored.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| Personal challenges | Creativity barriers Autonomy limitations | Standardized AI-generated content may restrain originality. AI reliance might discourage independent learning strategies. | 9 6 | 5.8 3.9 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| Social challenges | Reduced human interaction Communication barriers | AI-driven learning may limit peer collaboration and teacher-student engagement. Overuse of AI-based communication tools may affect interpersonal skills. | 8 3 | 5.2 1.9 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and student motivation.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“promotes personalized instruction”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| | Teacher resistance | Lack of familiarity or skepticism can hinder AI adoption. | 19 | 12.3 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| | Digital dependence | Over-reliance on AI may weaken traditional problem-solving skills and creativity. | 17 | 11.0 |”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“These tools have rapidly redefined educational practices by introducing new possibilities for teaching, learning, and assessment [22].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 2. Related Work
What the sources say
- Not checked yetcites [22] Mao, 2024, Generative Artificial Intelligence in Education and Its Implications for Assessment, TechTrends source
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Universities often serve as testing grounds for new technologies due to the presence of research expertise, ethical oversight, and a student population that may be more comfortable engaging with experimental digital tools [49].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.4. Education Level
What the sources say
- Not checked yetcites [49] Carayannis, 2022, The Futures of Europe: Society 5.0 and Industry 5.0 as Driving Forces of Future Universities, J. Knowl. Econ. source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“This approach, which is recommended in systematic review methodology to enhance the completeness of study identification [38], allowed us to identify 435 potential studies for inclusion in the final analysis.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 3.1. Planning the Review
What the sources say
- Not checked yetcites [38] Higgins, J.P.T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M.J., and Welch, V.A. (2019). Cochrane Handbook for Systematic Reviews of Interventions: Second Edition, John Wiley & Sons. source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“This reflects a paradigm shift rather than a temporary spike, reinforcing findings from recent reviews that describe AI as an increasingly integral component of pedagogical design, personalized learning, and assessment strategies [11,32,42].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.1. Publication Year
What the sources say
- Not checked yetcites [11] Strielkowski, 2024, AI-driven Adaptive Learning for Sustainable Educational Transformation, Sustain. Dev. source
- Not checked yetcites [32] Ayeni, 2024, AI in Education: A Review of Personalized Learning and Educational Technology, GSC Adv. Res. Rev. source
- Not checked yetcites [42] Halkiopoulos, C., and Gkintoni, E. (2024). Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis. Electronics, 13. source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The steady growth into 2024 suggests that AI is transitioning from an emergent innovation to a core element of educational research and practice.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.1. Publication Year
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“This spike likely correlates with the widespread release and adoption of generative AI tools, such as ChatGPT, which induced academic interest and application development [40,41].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.1. Publication Year
What the sources say
- Not checked yetcites [40] Lo, 2024, The Influence of ChatGPT on Student Engagement: A Systematic Review and Future Research Agenda, Comput. Educ. source
- Not checked yetcites [41] Kim, 2025, AI for Academic Success: Investigating the Role of Usability, Enjoyment, and Responsiveness in ChatGPT Adoption, Educ. Inf. Technol. source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The release of ChatGPT and subsequent generative AI systems marked a milestone in education, ushering in the post-ChatGPT era.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, they do not address the vast changes that have been posed by technologies such as ChatGPT, Gemini, Copilot, and DeepSeek, among others.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 2. Related Work
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The release of ChatGPT and subsequent generative AI systems marked a milestone in education, ushering in the post-ChatGPT era.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The review reveals a significant increase in research activity since 2022, reflecting the impact of generative AI tools, such as ChatGPT.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The release of ChatGPT and subsequent generative AI systems marked a milestone in education, ushering in the post-ChatGPT era.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These findings show AI's potential to enhance education; however, its success depends on careful implementation and collaboration among educators, researchers, and policymakers to ensure meaningful and equitable outcomes.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > Abstract
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“This imbalance may stem from structural challenges, such as limited research funding, unequal access to AI tools, or publication barriers faced by scholars in the Global South [45].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.2. Country of the Study
What the sources say
- Not checked yetcites [45] Rigley, 2024, Evaluating International AI Skills Policy: A Systematic Review of AI Skills Policy in Seven Countries, Glob. Policy source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“While these reviews offer valuable contributions, the studies they analyzed cover research conducted up to 2022.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 2. Related Work
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As a result, the current body of literature risks overrepresenting educational priorities, pedagogical models, and technological infrastructures from high-income or tech-dominant countries.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.2. Country of the Study
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At the same time, the presence of studies in a wide range of journals suggests that interest in this topic is expanding across diverse subfields, including learning analytics, personalized learning, and intelligent tutoring systems.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.3. Publication Journal
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“On the other hand, the relatively low number of studies at the primary and secondary levels may be influenced by a range of barriers, including ethical concerns related to minors, curricular rigidity, limited technical infrastructure in schools, and the perceived risks associated with deploying emerging technologies in early education [50,51].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.4. Education Level
What the sources say
- Not checked yetcites [50] Mintz, 2023, Artificial Intelligence and K-12 Education: Possibilities, Pedagogies and Risks, Comput. Sch. source
- Not checked yetcites [51] Kurian, 2025, AI’s Empathy Gap: The Risks of Conversational Artificial Intelligence for Young Children’s Well-Being and Key Ethical Considerations for Early Childhood Education and Care, Contemp. Issues Early Child. source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, the confidence in our thematic findings varies depending on the consistency and clarity of reporting across studies.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 5. Limitations of the Study and Future Work
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Ethical concerns and teacher resistance emerged as the most prominent challenges, indicating that the human dimensions of AI adoption, such as privacy, bias, and user acceptance, remain critical barriers.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“This gap supports critiques raised by Sethi and Jain [60] and Zheng et al. [61], who argue that many AI applications in education tend to prioritize individualized learning over collaborative and socio-emotional learning.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
What the sources say
- Not checked yetcites [60] Sethi, 2024, AI Technologies for Social Emotional Learning: Recent Research and Future Directions, J. Res. Innov. Teach. Learn. source
- Not checked yetcites [61] Zheng, 2024, Using AI-Empowered Assessments and Personalized Recommendations to Promote Online Collaborative Learning Performance, J. Res. Technol. Educ. source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“The prevalence of Conversational and NLP Agents reflects sustained interest in dialogue-based learning tools for language acquisition and tutoring, consistent with prior findings on chatbot-mediated instruction [29].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.6. Type of AI
What the sources say
- Not checked yetcites [29] Wang, 2024, Does Chatting with Chatbots Improve Language Learning Performance? A Meta-Analysis of Chatbot-Assisted Language Learning, Rev. Educ. Res. source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“Studies show that teachers who are unfamiliar with AI often view it as a threat rather than a tool to enhance learning [62,63].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
What the sources say
- Not checked yetcites [62] Jevsikova, 2024, Key Factors Influencing Teachers’ Motivation to Transfer Technology-Enabled Educational Innovation, Educ. Inf. Technol. source
- Not checked yetcites [63] Alwaqdani, 2025, Investigating Teachers’ Perceptions of Artificial Intelligence Tools in Education: Potential and Difficulties, Educ. Inf. Technol. source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Social challenges, including reduced human interaction and communication barriers, suggest that AI may compromise the relational aspects of education, another area previously identified as underdeveloped in AI-enhanced learning environments.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“The prominence of language-related studies reflects a growing interest in the application of AI for personalized and adaptive instruction, particularly through technologies such as intelligent tutoring systems, generative AI, automated feedback tools, and speech recognition [53,54].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.5. Education Field
What the sources say
- Not checked yetcites [53] Son, 2025, Artificial Intelligence Technologies and Applications for Language Learning and Teaching, J. China Comput. Lang. Learn.
- Not checked yetcites [54] Dai, 2024, Leveraging Artificial Intelligence (AI) in English as a Foreign Language (EFL) Classes: Challenges and Opportunities in the Spotlight, Comput. Human Behav. source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Notably, 2.6% of studies lacked sufficient details to classify AI type, highlighting gaps in reporting standards.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.6. Type of AI
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“These outcomes reflect AI's potential to foster higher-order thinking through mechanisms such as real-time feedback, interactive simulations, and scaffolded learning experiences [58].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
What the sources say
- Not checked yetcites [58] Erdogan, 2025, Influence of Artificial Intelligence Tools on Higher Order Thinking Skills: A Meta-Analysis, Interact. Learn. Environ. source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, the relatively limited attention to teacher-centered benefits points to a persistent gap in research and development.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Teachers are essential mediators of AI adoption.
In the paper
“The substantial representation of ICT aligns with prior literature that identifies a natural synergy between AI and computer science education [55].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.5. Education Field
What the sources say
- Not checked yetcites [55] Liu, R., Zenke, C., Liu, C., Holmes, A., Thornton, P., and Malan, D.J. (2024, January 20–23). Teaching CS50 with AI: Leveraging Generative Artificial Intelligence in Computer Science Education. Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1, New York, NY, USA. source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“This aligns with recent literature indicating a surge in generative AI adoption in education due to its versatility in producing personalized content and feedback [40,41].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.6. Type of AI
What the sources say
- Not checked yetcites [40] Lo, 2024, The Influence of ChatGPT on Student Engagement: A Systematic Review and Future Research Agenda, Comput. Educ. source
- Not checked yetcites [41] Kim, 2025, AI for Academic Success: Investigating the Role of Usability, Enjoyment, and Responsiveness in ChatGPT Adoption, Educ. Inf. Technol. source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Meanwhile, Embodied and Immersive Systems and Intelligent Tutoring Systems remain less frequent, despite strong evidence of their effectiveness in fostering engagement and deep learning [32].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.6. Type of AI
What the sources say
- Not checked yetcites [32] Ayeni, 2024, AI in Education: A Review of Personalized Learning and Educational Technology, GSC Adv. Res. Rev. source
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“First, we excluded grey literature, such as conference papers, dissertations, and policy reports.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 5. Limitations of the Study and Future Work
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Challenges such as creativity barriers and autonomy limitations suggest that overstandardization in AI-driven content may inhibit learner agency and originality.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“While this decision ensured a focus on peer-reviewed studies, it may have led to the exclusion of emerging or context-specific insights not yet captured in journal publications.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 5. Limitations of the Study and Future Work
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This broader categorization reveals significant imbalances in how AI's potential is being used, particularly the relative neglect of social-emotional, collaborative, and teacher-related dimensions.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“On the personal dimension, benefits such as increased motivation, autonomy, and engagement suggest that AI-supported environments often enhance students' affective and behavioral responses to learning.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
hedgedconditional- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Technical difficulties and low digital literacy among teachers further reflect infrastructural and competence-related barriers that may hinder the effective deployment of AI tools, reinforcing similar concerns raised in the literature about the digital divide in both student and teacher populations.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
hedgedconditional- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The relatively small portion of Rule-Based & Expert Systems reflects a shift from static, deterministic systems toward adaptive and data-driven approaches.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.6. Type of AI
plaindirect- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The minimal attention to cultural awareness further suggests that the design of AI tools has not yet fully incorporated culturally responsive pedagogy or global competencies, which are increasingly relevant in today's interconnected educational landscape.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
hedgedconditional- Asserted: passes — The authors put it forward as true.
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What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“the heterogeneity in study designs and limited methodological reporting in some cases reduce our overall ability to evaluate certainty systematically.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 5. Limitations of the Study and Future Work
plaindirect- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“suggesting a research gap in socially driven and educator-focused AI applications.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
hedged- Asserted: passes — The authors put it forward as true.
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- It may state two separate claims as one. 30
- Probably not a substantial claim. 31
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Studies highlight a range of benefits, including enhanced learning outcomes, personalized instruction, and increased student motivation.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, there are challenges to overcome, such as students' ethical use of AI, teachers' resistance to using AI systems, and the digital dependency these systems can generate.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > Abstract
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In contrast, the number of studies conducted at the primary, secondary, and teacher education levels was notably lower and relatively evenly distributed.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.4. Education Level
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The studies were conducted in 35 countries from all inhabited continents.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.2. Country of the Study
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“Studies in this area often involve teaching students about AI itself or using AI to support algorithmic thinking, coding instruction, or learning analytics [56].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.5. Education Field
What the sources say
- Not checked yetcites [56] Huang, 2024, Enhancing Computational Thinking Skills Through Artificial Intelligence Education at a STEAM High School, Sci. Educ. source
plaincorrelational- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Other frequently reported cognitive benefits include improvements in problemsolving, knowledge retention, and critical thinking.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
plaincorrelational- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Specifically, many educators resist adopting AI due to skepticism, lack of trust, fear of job displacement, or a reluctance to change their teaching methods.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Ethical concerns and teacher resistance emerged as the most prominent challenges, indicating that the human dimensions of AI adoption, such as privacy, bias, and user acceptance, remain critical barriers.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Meanwhile, Embodied and Immersive Systems and Intelligent Tutoring Systems remain less frequent, despite strong evidence of their effectiveness in fostering engagement and deep learning [32].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.6. Type of AI
plain- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There is a strong dominance of language learning, followed by ICT and science education.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.5. Education Field
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“For example, cognitive and motivational benefits of AI were frequently reported across multiple contexts and supported by converging evidence, suggesting moderate to high confidence in these themes.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 5. Limitations of the Study and Future Work
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The analysis shows that Generative AI was the most implemented type, followed by Conversational and NLP Agents, and Machine Learning Models.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.6. Type of AI
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The results show a multifaceted range of challenges associated with integrating AI into educational environments, with personal and teacher-related concerns being the most frequently reported.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“While all included studies were peer-reviewed”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 5. Limitations of the Study and Future Work
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The findings reveal a significant increase in AI-related educational research, especially from 2023 onward, coinciding with the widespread release of tools such as ChatGPT.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
plaincorrelational- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Occasional discrepancies in this process were resolved through consensus.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > Studies Were Included if They:
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Before synthesizing the findings, we carefully reviewed all extracted data to ensure they were complete and consistent.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 3.3. Reporting the Review
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“A standardized data extraction form was developed by the research team to ensure consistency in coding and interpretation.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 3.2. Conducting the Review
plaindirect- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The themes were identified through iterative comparison, and disagreements were resolved in consultation with the first author.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 3.2. Conducting the Review
plain- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The predominance of higher education in AI-related research aligns with prior reviews in the field of educational technology, which attribute this trend to the increased availability of digital infrastructure, funding mechanisms, and institutional autonomy in universities [36].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.4. Education Level
What the sources say
- Not checked yetcites [36] Guo, 2024, Artificial Intelligence in Education Research during 2013–2023: A Review Based on Bibliometric Analysis, Educ. Inf. Technol. source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“This protocol was developed internally by the research team during the planning stage and registered on the Open Science Framework (OSF) platform.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 3.1. Planning the Review
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The concentration of publications in these high-impact journals highlights the growing academic recognition of AI's transformative potential in education.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.3. Publication Journal
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Although the form was not formally piloted, it was collaboratively refined during the initial phase of data extraction.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 3.2. Conducting the Review
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The second and third authors independently coded the extracted qualitative data manually using Microsoft Excel.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 3.2. Conducting the Review
plain- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“This diversity suggests that the topic transcends traditional disciplinary boundaries, attracting attention from both educational technology specialists and researchers in broader pedagogical and computational domains [37].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.3. Publication Journal
What the sources say
- Not checked yetcites [37] Wang, 2024, Artificial Intelligence in Education: A Systematic Literature Review, Expert Syst. Appl. source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The uneven geographic representation raises concerns about whether AI tools can effectively meet the diverse needs of educational systems worldwide.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.2. Country of the Study
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the paper
“Without including diverse educational contexts, it is difficult to ensure that AI solutions are adaptable, ethical, and relevant on a global scale [46,47].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.2. Country of the Study
What the sources say
- Not checked yetcites [46] Holmes, W., Bialik, M., and Fadel, C. (2023). Artificial Intelligence in Education. Data Ethics: Building Trust: How Digital Technologies can Serve Humanity, Globethics Publications. source
- Not checked yetcites [47] Yambal, S., and Waykar, Y.A. (2025). Future of Education Using Adaptive AI, Intelligent Systems, and Ethical Challenges, IGI Global Scientific Publishing. source
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Rests on an assumption: Educational systems differ widely in terms of language, infrastructure, curricula, and student needs.
None of the sources cited for this claim have been checked yet.
In the paper
“This systematic review adopted the PRISMA statement approach [34] and followed the recommendations of Kitchenham and Charters [35].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 3. Methods
What the sources say
- Not checked yetcites [34] Page, 2021, The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews, Syst. Rev. source
- Not checked yetcites [35] Kitchenham, B., and Charters, S. (2007). Guidelines for Performing Systematic Literature Reviews in Software Engineering Version 2.3.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In cases where certain descriptive details, such as the country of origin, were not explicitly provided, we used the first author's affiliation as a proxy.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 3.3. Reporting the Review
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Although several reviews have explored AI's role in education, most are limited to pre-ChatGPT publications or narrow scopes focused on specific applications, user groups, pedagogical models, or types of AI systems.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 1. Introduction
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“If the second and third authors disagreed on any specific paper, the first author reviewed the paper and made the final decision to maintain consistency and rigor.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > Studies Were Included if They:
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Without such guidance, there is a risk that AI may be applied inconsistently or inequitably as its adoption increases [43,44].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.1. Publication Year
What the sources say
- Not checked yetcites [43] Costa, C.J., Aparicio, M., Aparicio, S., and Aparicio, J.T. (2024). The Democratization of Artificial Intelligence: Theoretical Framework. Appl. Sci., 14. source
- Not checked yetcites [44] Zou, 2025, Navigating the Future: Establishing a Framework for Educators’ Pedagogic Artificial Intelligence Competence, Eur. J. Educ. source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“To support meaningful comparisons across studies, we standardized education levels and subject areas using the International Standard Classification of Education (ISCED).”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 3.3. Reporting the Review
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Third, although the results raised ethical concerns and digital dependency, we do not thoroughly examine the long-term consequences of AI integration, such as changes in teacher roles, student autonomy, or institutional policies.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 5. Limitations of the Study and Future Work
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“This aligns with previous studies, such as those by Strielkowski et al. [11] and Xu [57], which emphasize the transformative potential of AI in improving academic outcomes through adaptive learning environments.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
What the sources say
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Furthermore, this review did not apply a formal framework to assess the certainty of the evidence for each outcome.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 5. Limitations of the Study and Future Work
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These tools offer solutions to language learning challenges, such as vocabulary acquisition, grammar correction, and pronunciation feedback, which may explain their popularity among researchers.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.5. Education Field
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“As such, the findings may slightly overrepresent more established academic perspectives and underrepresent practitioner-driven innovations.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 5. Limitations of the Study and Future Work
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This trend is not surprising given that many AI applications originate within ICT-related fields and are often conducted by technically proficient educators or within computing departments.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.5. Education Field
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Rests on an assumption: Many AI applications originate within ICT-related fields and are often conducted by technically proficient educators or within computing departments.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Second, while the review identifies general benefits and challenges of AI in education, it does not deeply explore how different AI applications align with specific pedagogical models or teaching strategies across disciplines and contexts.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 5. Limitations of the Study and Future Work
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Additionally, implementing AI in these contexts often requires adaptations to pedagogy and content, which may dissuade rapid experimentation.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.4. Education Level
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“These findings are consistent with previous studies [64,65], which emphasize that trust, transparency, and ethical governance are foundational for the successful use of AI in education.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
What the sources say
- Not checked yetcites [64] Shukla, 2024, Principles Governing Ethical Development and Deployment of AI, Int. J. Eng. Bus. Manag. source
- Not checked yetcites [65] Fu, 2024, Navigating the Ethical Terrain of AI in Education: A Systematic Review on Framing Responsible Human-Centered AI Practices, Comput. Educ. Artif. Intell. source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These dualities, where certain factors are reported as strengths and weaknesses, highlight the importance of considering contextual, technological, and individual variables when evaluating AI's impact.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the paper
“Compared to earlier studies [19,37], this analysis offers a deeper categorization and highlights the tension between AI's potential and its limitations.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
What the sources say
- Not checked yetcites [19] Dimitriadou, 2023, A Critical Evaluation, Challenges, and Future Perspectives of Using Artificial Intelligence and Emerging Technologies in Smart Classrooms, Smart Learn. Environ. source
- Not checked yetcites [37] Wang, 2024, Artificial Intelligence in Education: A Systematic Literature Review, Expert Syst. Appl. source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“These findings align with research by Younas et al. [59] and Wang et al. [37], which have also found that intelligent tutoring systems and gamified AI applications promote student interest and self-directed learning.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
What the sources say
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Our classification of AI benefits into cognitive, personal, social, and teacher domains offers a more comprehensive framework than earlier reviews [16][17][18][19][20][21], which often focused narrowly on learning outcomes.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
What the sources say
- Not checked yetcites [16][17][18][19][20][21]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These gaps point to potential missed opportunities for innovation.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.5. Education Field
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Given that teachers play a central role in mediating the integration of AI into classrooms, this gap underlines a critical area for future research.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1.4. Education Level
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Rests on an assumption: Teachers play a central role in mediating the integration of AI into classrooms.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“From a cognitive perspective, digital dependence and increased anxiety point to potential unintended consequences of AI overuse, such as reduced creativity and heightened psychological stress, particularly when AI systems are poorly designed or overly focused on assessment.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“These challenges have been highlighted by researchers such as Strielkowski et al. [11], who caution against overly technocentric approaches that neglect pedagogical and emotional considerations.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.3. Challenges Associated with AI in Education
What the sources say
- Not checked yetcites [11] Strielkowski, 2024, AI-driven Adaptive Learning for Sustainable Educational Transformation, Sustain. Dev. source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These findings suggest that AI is widely perceived as a powerful tool for personalizing instruction, adapting to individual learning needs, and fostering student engagement.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“These results align with studies that demonstrate how AI can streamline administrative duties, generate personalized learning analytics, and support instructional planning [15,17].”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
What the sources say
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Additionally, benefits like digital literacy and accessibility demonstrate AI's role in equipping students with essential 21st-century skills and making learning more inclusive for diverse populations.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.2. Benefits Associated with AI in Education
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
Teachers play a central role in mediating the integration of AI into classrooms.
“Given that teachers play a central role in mediating the integration of AI into classrooms, this gap underlines a critical area for future research.”
The paper relies on this without support.
The release of ChatGPT and subsequent generative AI systems marked a milestone in education, ushering in the post-ChatGPT era.
“The release of ChatGPT and subsequent similar generative AI systems, such as DeepSeek, Claude, Gemini, and Copilot, has marked a milestone in education, ushering in what might be called the post-ChatGPT era.”
The paper relies on this without support.
Educational systems differ widely in terms of language, infrastructure, curricula, and student needs.
“Educational systems differ widely in terms of language, infrastructure, curricula, and student needs.”
The paper relies on this without support.
Many AI applications originate within ICT-related fields and are often conducted by technically proficient educators or within computing departments.
“This trend is not surprising given that many AI applications originate within ICT-related fields and are often conducted by technically proficient educators or within computing departments.”
The paper relies on this without support.
Educators play a central role in mediating the implementation of AI tools.
“This is notable given the central role of educators in mediating the implementation of AI tools.”
The paper relies on this without support.
Teachers are essential mediators of AI adoption.
“Given that teachers are essential mediators of AI adoption, more work is needed to empower educators with tools that enhance, not replace, their professional agency and pedagogical expertise.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, the central boundary condition is that learning benefits depend on how learners interact with mediation—when students engage with AI outputs by questioning, comparing drafts, rejecting or adapting suggestions, and justifying compositional choices, the interaction constitutes active mediated learning rather than passive text transfer (Garzón et al., 2025; Ilgun Dibek et al., 2025).”
From From tool to scaffold: structured human–AI collaboration and its effects on academic writing and digital critical thinking among Saudi EFL learners (2026) · cites this paper as Garzón et al., 2025
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Systematic reviews of AI in education describe accelerating use of AI tools for adaptive learning, intelligent tutoring, automated assessment feedback, and writing support, with reported associations to enhanced learner engagement, higher feedback quality, and a broad range of cognitive outcomes (Garzón et al., 2025; Ilgun Dibek et al., 2025).”
From From tool to scaffold: structured human–AI collaboration and its effects on academic writing and digital critical thinking among Saudi EFL learners (2026) · cites this paper as Garzón et al., 2025
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 6. Conclusions
“This systematic literature review examined 132 empirical studies published between 2015 and 2024 to identify the prevailing trends, benefits, and challenges of integrating AI in educational environments.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > Abstract
“This review analyzed 155 peer-reviewed empirical studies published between 2015 and 2025.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 4.1. Trends Characterizing the Current Research on AI in Education
“We examined five key dimensions: publication year, country of study, publication journal, educational level, education field, and AI type.”
§ Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges > 1. Introduction
“This question examines trends in publication year, the country where the study was conducted, the journal in which the study was published, the educational level at which the study was implemented, the educational field involved in the study, and the type of artificial intelligence system implemented in the study.”
Citations
Cites
Cochrane Handbook for Systematic Reviews of Interventions
(2019) · doi:10.1002/9781119536604 · Cited by 14,828
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · Systematic Reviews · doi:10.1186/s13643-021-01626-4 · Cited by 13,874 · cited 1×
“This systematic review adopted the PRISMA statement approach [34] and followed the recommendations of Kitchenham and Charters [35].”
Weighted kappa: nominal scale agreement provision for scaled disagreement or partial credit
Cohen, J. (1968) · Psychological Bulletin · doi:10.1037/h0026256 · Cited by 8,736 · cited 1×
“This value was 0.89, indicating almost perfect agreement [39].”
InfluentialArtificial Intelligence in Education: A Review
Chen, L., Chen, P., & Lin, Z. (2020) · IEEE Access · doi:10.1109/access.2020.2988510 · Cited by 4,133 · cited 3×
“In addition to database search, we conducted backward citation searching by re-viewing the reference lists of relevant prior systematic reviews [14,16–19, 26, After removing 1838 duplicate entries, the second and third authors screened the remaining studies ( n = 2003 ) based on their titles,…”
A Review of Artificial Intelligence (AI) in Education from 2010 to 2020
Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2021) · Complexity · doi:10.1155/2021/8812542 · Cited by 1,364 · cited 2×
“The review by Zhai et al. [17] categorized educational AI research into three dimensions: development (e.g., intelligent tutoring systems and adaptive learning models), extraction (e.g., feedback and reasoning), and application (e.g., immersive learning and gamification).”
Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100118 · Cited by 1,181 · cited 2×
“Chiu et al. [18] examined the scattered nature of research in educational AI and proposed a framework that categorizes AI applications into four key domains: learning, teaching, assessment, and administration.”
State of the art and practice in AI in education
Holmes, W., & Tuomi, I. (2022) · European Journal of Education · doi:10.1111/ejed.12533 · Cited by 1,093 · cited 2×
“These results align with studies that demonstrate how AI can streamline administrative duties, generate personalized learning analytics, and support instructional planning [15,17].”
Artificial Intelligence in Education: A Systematic Literature Review
Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.124167 · Cited by 977 · cited 4×
“This diversity suggests that the topic transcends traditional disciplinary boundaries, attracting attention from both educational technology specialists and researchers in broader pedagogical and computational domains [37].”
InfluentialAbulibdeh, A. O., Zaidan, E., & Abulibdeh, R. (2024) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2023.140527 · Cited by 866 · cited 1×
“In educational contexts, AI is a branch of computer science that can perform tasks such as reasoning, decision-making, and learning, which are traditionally associated with human intelligence [4,5].”
Components of Education 4.0 in 21st Century Skills Frameworks: Systematic Review
González-Pérez, L. I., & Soledad, M. (2022) · Sustainability · doi:10.3390/su14031493 · Cited by 762 · cited 1×
“Educational environments, on the other hand, include the physical, social, and technological contexts in which learning occurs [6].”
Research works printed but not linked: 1
- Cole, M., John, V.-S., Scribner, S., and Souberman, E. (1978). Mind in Society: The Development of Higher Psychological Processes, Harvard University Press.
Cited by
Sorted by citations
Conceptualizing the Impact of AI on Teacher Knowledge and Expertise: A Cognitive Load Perspective
Rind, I. A. (2026) · Education Sciences · doi:10.3390/educsci16010057 · Cited by 27
Mapping the evolution of AI in education: Toward a co-adaptive and human-centered paradigm
Feng, S., Zhang, H., & Gašević, D. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100513 · Cited by 30
AI and the digital divide in education
Matjie, M. A., Nethavhani, A., & Matlakala, M. (2026) · Frontiers in Computer Science · doi:10.3389/fcomp.2026.1759027 · Cited by 46
“AI should change learning for all learners across the globe (Luckin et al., 2016; Selwyn and Facer, 2013); however, that is not always the case (Garzón et al., 2025; Krause et al., 2024).”
Ansari, S. R., & Qamari, I. N. (2025) · Discover Education · doi:10.1007/s44217-025-00865-0 · Cited by 36
“These findings are consistent with Garzón et al. 2025 [23], who, in their systematic review of AI in education from 2015 to 2025, similarly reported a significant surge in publications beginning in 2022, particularly driven by generative AI applications such as ChatGPT.”
Adaptive and Personalized Learning in Higher Education: An Artificial Intelligence-Based Approach
Hernández-Herrera, J. R., Ortiz-Bejar, J., & Ortiz-Bejar, J. (2026) · Education Sciences · doi:10.3390/educsci16010109 · Cited by 22
Metadata
- Authors
- Garzón, J., Patiño, E., & Marulanda, C.
- Affiliations
- Universidad Católica de Oriente (CO)
- Corresponding author
- Garzón, Juan
- Venue
- Multimodal Technologies and Interaction
- Publisher
- MDPI AG
- Published
- 2025-08-20
- Volume
- 9
- Issue
- 8
- Pages
- 84
- ISSN
- 2414-4088 (ISSN-L)
- OpenAlex
- W4413401681
- Semantic Scholar
- 594051870a74e72b85f42c7f52be0954184c81ca
- Cited by
- 265
- References
- 65
- Citations by year
- 2026: 238 · 2025: 27
- FWCI
- 40.73
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Multimodal Technologies and Interaction (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- artificial intelligence in education, generative AI, ChatGPT, personalized instruction, student motivation, learning outcomes, ethical use of AI, digital dependence, research trends, educational equity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-09, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-09 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
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