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Evidence registry · 119 sources

Master bibliography

Every numbered citation in the manuscript resolves to an entry here. DOI links are preferred where available; institutional reports link to their authoritative publication page. Some reports use their main title without the subtitle; linked records retain full publication details.

  1. nasem-hpl2-2018

    National Academies of Sciences, Engineering, and Medicine (2018).

    How People Learn II: Learners, Contexts, and Cultures

    The National Academies Press

    doi:10.17226/24783
  2. dunlosky-2013

    Dunlosky, John; Rawson, Katherine A.; Marsh, Elizabeth J.; Nathan, Mitchell J.; Willingham, Daniel T. (2013).

    Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology

    Psychological Science in the Public Interest, 14, (1), 4–58

    doi:10.1177/1529100612453266
  3. cepeda-2006

    Cepeda, Nicholas J.; Pashler, Harold; Vul, Edward; Wixted, John T.; Rohrer, Doug (2006).

    Distributed Practice in Verbal Recall Tasks: A Review and Quantitative Synthesis

    Psychological Bulletin, 132, (3), 354–380

    doi:10.1037/0033-2909.132.3.354
  4. roediger-karpicke-2006

    Roediger, Henry L. III; Karpicke, Jeffrey D. (2006).

    Test-Enhanced Learning: Taking Memory Tests Improves Long-Term Retention

    Psychological Science, 17, (3), 249–255

    doi:10.1111/j.1467-9280.2006.01693.x
  5. freeman-2014

    Freeman, Scott; Eddy, Sarah L.; McDonough, Miles; et al. (2014).

    Active Learning Increases Student Performance in Science, Engineering, and Mathematics

    Proceedings of the National Academy of Sciences, 111, (23), 8410–8415

    doi:10.1073/pnas.1319030111
  6. barnett-ceci-2002

    Barnett, Susan M.; Ceci, Stephen J. (2002).

    When and Where Do We Apply What We Learn? A Taxonomy for Far Transfer

    Psychological Bulletin, 128, (4), 612–637

    doi:10.1037/0033-2909.128.4.612
  7. deci-ryan-2000

    Deci, Edward L.; Ryan, Richard M. (2000).

    The ‘What’ and ‘Why’ of Goal Pursuits: Human Needs and the Self-Determination of Behavior

    Psychological Inquiry, 11, (4), 227–268

    doi:10.1207/S15327965PLI1104_01
  8. immordino-yang-2007

    Immordino-Yang, Mary Helen; Damasio, Antonio (2007).

    We Feel, Therefore We Learn: The Relevance of Affective and Social Neuroscience to Education

    Mind, Brain, and Education, 1, (1), 3–10

    doi:10.1111/j.1751-228X.2007.00004.x
  9. lee-2018

    Lee, James J; Wedow, Robbee; Okbay, Aysu; et al. (2018).

    Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

    Nature genetics, 50, (8), 1112-1121

    doi:10.1038/s41588-018-0147-3
  10. kong-2018

    Kong, Augustine; Thorleifsson, Gudmar; Frigge, Michael L; et al. (2018).

    The nature of nurture: Effects of parental genotypes

    Science (New York, N.Y.), 359, (6374), 424-428

    doi:10.1126/science.aan6877
  11. cast-udl-2024

    CAST (2024).

    Universal Design for Learning Guidelines, Version 3.0

    CAST

    View authoritative source
  12. kraft-2018

    Kraft, Matthew A.; Blazar, David; Hogan, Dylan (2018).

    The Effect of Teacher Coaching on Instruction and Achievement: A Meta-Analysis of the Causal Evidence

    Review of Educational Research, 88, (4), 547–588

    doi:10.3102/0034654318759268
  13. oecd-talis-2019

    OECD (2019).

    TALIS 2018 Results (Volume I): Teachers and School Leaders as Lifelong Learners

    OECD Publishing

    doi:10.1787/1d0bc92a-en
  14. nrc-testing-2011

    National Research Council (2011).

    Incentives and Test-Based Accountability in Education

    The National Academies Press

    doi:10.17226/12521
  15. oecd-pisa-2023

    OECD (2023).

    PISA 2022 Results (Volume I)

    OECD Publishing

    doi:10.1787/53f23881-en
  16. black-wiliam-1998

    Black, Paul; Wiliam, Dylan (1998).

    Assessment and Classroom Learning

    Assessment in Education: Principles, Policy & Practice, 5, (1), 7–74

    doi:10.1080/0969595980050102
  17. hattie-timperley-2007

    Hattie, John; Timperley, Helen (2007).

    The Power of Feedback

    Review of Educational Research, 77, (1), 81–112

    doi:10.3102/003465430298487
  18. durlak-2011

    Durlak, Joseph A.; Weissberg, Roger P.; Dymnicki, Allison B.; Taylor, Rebecca D.; Schellinger, Kriston B. (2011).

    The Impact of Enhancing Students’ Social and Emotional Learning: A Meta-Analysis of School-Based Universal Interventions

    Child Development, 82, (1), 405–432

    doi:10.1111/j.1467-8624.2010.01564.x
  19. nist-privacy-2020

    National Institute of Standards and Technology (2020).

    NIST Privacy Framework: A Tool for Improving Privacy Through Enterprise Risk Management, Version 1.0

    NIST

    View authoritative source
  20. nist-ai-rmf-2023

    Tabassi, Elham (2023).

    Artificial Intelligence Risk Management Framework (AI RMF 1.0)

    National Institute of Standards and Technology

    doi:10.6028/NIST.AI.100-1
  21. unesco-ai-2023

    Miao, Fengchun; Holmes, Wayne (2023).

    Guidance for Generative AI in Education and Research

    UNESCO

    doi:10.54675/EWZM9535
  22. usdoe-ai-2023

    U.S. Department of Education, Office of Educational Technology (2023).

    Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations

    U.S. Department of Education

    View authoritative source
  23. unesco-gem-2023

    Global Education Monitoring Report Team (2023).

    Global Education Monitoring Report 2023: Technology in Education: A Tool on Whose Terms?

    UNESCO

    View authoritative source
  24. itu-2025

    International Telecommunication Union (2025).

    Measuring Digital Development: Facts and Figures 2025

    ITU

    View authoritative source
  25. worldbank-learning-poverty-2022

    World Bank; UNICEF; FCDO; USAID; UNESCO (2022).

    The State of Global Learning Poverty: 2022 Update

    World Bank

    View authoritative source
  26. chetty-2022

    Chetty, Raj; Jackson, Matthew O; Kuchler, Theresa; et al. (2022).

    Social capital II: determinants of economic connectedness

    Nature, 608, (7921), 122-134

    doi:10.1038/s41586-022-04997-3
  27. sala-gobet-2017

    Sala, Giovanni; Gobet, Fernand (2017).

    When the Music’s Over: Does Music Skill Transfer to Children’s and Young Adolescents’ Cognitive and Academic Skills? A Meta-Analysis

    Educational Research Review, 20, 55–67

    doi:10.1016/j.edurev.2016.11.005
  28. lehtonen-2018

    Lehtonen, Minna; Soveri, Anna; Laine, Aini; Järvenpää, Janne; de Bruin, Angela; Antfolk, Jan (2018).

    Is Bilingualism Associated With Enhanced Executive Functioning in Adults? A Meta-Analytic Review

    Psychological Bulletin, 144, (4), 394–425

    doi:10.1037/bul0000142
  29. means-2010

    Means, Barbara; Toyama, Yukie; Murphy, Robert; Bakia, Marianne; Jones, Karla (2010).

    Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies

    U.S. Department of Education

    View authoritative source
  30. idea-2004

    United States Congress (2004).

    Individuals with Disabilities Education Act

    U.S. Department of Education

    View authoritative source
  31. bastani-2025

    Bastani, Hamsa; Bastani, Osbert; Sungu, Alp; Ge, Haosen; Kabakcı, Özge; Mariman, Rei (2025).

    Generative AI without guardrails can harm learning: Evidence from high school mathematics

    Proceedings of the National Academy of Sciences, 122, (26), e2422633122

    doi:10.1073/pnas.2422633122
  32. kestin-2025

    Kestin, Greg; Miller, Kelly; Klales, Anna; Milbourne, Timothy; Ponti, Gregorio (2025).

    AI Tutoring Outperforms In-Class Active Learning: An RCT Introducing a Novel Research-Based Design in an Authentic Educational Setting

    Scientific Reports, 15, 17458

    doi:10.1038/s41598-025-97652-6
  33. shi-2026

    Shi, Y.; Yu, S.; Dong, Y.; Chen, S. (2026).

    Large Language Models in Education: A Systematic Review of Empirical Applications, Benefits, and Challenges

    Computers and Education: Artificial Intelligence, 10, 100529

    doi:10.1016/j.caeai.2025.100529
  34. wang-2026-ai-feedback

    Wang, Wenxuan; Wang, Yiting; Chen, Jiahua; et al. (2026).

    The Effectiveness of AI-Supported Personalized Feedback on Students’ Learning Outcomes and Motivation: A Meta-Analysis

    Journal of Educational Computing Research, 64, (3), 724–755

    doi:10.1177/07356331251410020
  35. mohammadi-2025

    Mohammadi, Mehrnoush; Tajik, Elham; Martinez-Maldonado, Roberto; Sadiq, Shazia; Tomaszewski, Wojtek; Khosravi, Hassan (2025).

    Artificial Intelligence in Multimodal Learning Analytics: A Systematic Literature Review

    Computers and Education: Artificial Intelligence, 8, 100426

    doi:10.1016/j.caeai.2025.100426
  36. zhang-aslan-2021

    Zhang, K.; Aslan, Ayse Begum (2021).

    AI Technologies for Education: Recent Research and Future Directions

    Computers and Education: Artificial Intelligence, 2, 100025

    doi:10.1016/j.caeai.2021.100025
  37. roll-wylie-2016

    Roll, Ido; Wylie, Ruth (2016).

    Evolution and Revolution in Artificial Intelligence in Education

    International Journal of Artificial Intelligence in Education, 26, 582–599

    doi:10.1007/s40593-016-0110-3
  38. shute-2008

    Shute, Valerie J. (2008).

    Focus on Formative Feedback

    Review of Educational Research, 78, (1), 153–189

    doi:10.3102/0034654307313795
  39. agarwal-2021

    Agarwal, Pooja K.; Nunes, Ludmila D.; Blunt, Janell R. (2021).

    Retrieval Practice Consistently Benefits Student Learning: A Systematic Review of Applied Research in Schools and Classrooms

    Educational Psychology Review, 33, 1409–1453

    doi:10.1007/s10648-021-09595-9
  40. corral-carpenter-2025

    Corral, David; Carpenter, Shana K. (2025).

    Effects of Retrieval Practice on Retention and Application of Complex Educational Concepts

    Learning and Instruction, 100, 102219

    doi:10.1016/j.learninstruc.2025.102219
  41. murray-2025

    Murray, Ewan; Horner, Aidan J.; Göbel, Silke M. (2025).

    A Meta-analytic Review of the Effectiveness of Spacing and Retrieval Practice for Mathematics Learning

    Educational Psychology Review, 37, 75

    doi:10.1007/s10648-025-10035-1
  42. zimmerman-2002

    Zimmerman, Barry J. (2002).

    Becoming a Self-Regulated Learner: An Overview

    Theory Into Practice, 41, (2), 64–70

    doi:10.1207/S15430421TIP4102_2
  43. mayer-2008

    Mayer, Richard E. (2008).

    Applying the Science of Learning: Evidence-Based Principles for the Design of Multimedia Instruction

    American Psychologist, 63, (8), 760–769

    doi:10.1037/0003-066X.63.8.760
  44. sweller-2024

    Sweller, John (2024).

    Cognitive Load Theory and Individual Differences

    Learning and Individual Differences, 110, 102423

    doi:10.1016/j.lindif.2024.102423
  45. national-reading-panel-2000

    National Reading Panel (2000).

    Teaching Children to Read: An Evidence-Based Assessment of the Scientific Research Literature on Reading and Its Implications for Reading Instruction

    National Institute of Child Health and Human Development

    View authoritative source
  46. ies-foundational-reading-2016

    Foorman, Barbara; Beyler, Nicholas; Borradaile, Kelley; et al. (2016).

    Foundational Skills to Support Reading for Understanding in Kindergarten Through 3rd Grade

    National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education, NCEE 2016-4008

    View authoritative source
  47. kittle-2024

    Kittle, Jonathan M.; Amendum, Steven J.; Budde, Christina M. (2024).

    What Does Research Say About the Science of Reading for K-5 Multilingual Learners? A Systematic Review of Systematic Reviews

    Educational Psychology Review, 36, 108

    doi:10.1007/s10648-024-09942-6
  48. van-der-velde-2025

    van der Velde, Max; Harmsen, Wieke; Veldkamp, Bernard P.; Feskens, Remco; Keuning, Jos; Swart, Nicole (2025).

    Speech Enabled Reading Fluency Assessment: a Validation Study

    International Journal of Artificial Intelligence in Education, 35, 2569-2595

    doi:10.1007/s40593-025-00480-y
  49. molenaar-2023

    Molenaar, Bo; Tejedor-Garcia, Cristian; Cucchiarini, Catia; Strik, Helmer (2023).

    Automatic Assessment of Oral Reading Accuracy for Reading Diagnostics

    Interspeech 2023, 5232-5236

    doi:10.21437/Interspeech.2023-1681
  50. van-waes-2021

    Van Waes, Luuk; Leijten, Mariëlle; Roeser, Jens; Olive, Thierry; Grabowski, Joachim (2021).

    Measuring and Assessing Typing Skills in Writing Research

    Journal of Writing Research, 13, (1), 107-153

    doi:10.17239/jowr-2021.13.01.04
  51. gong-2022

    Gong, T.; Zhang, M.; Li, C. (2022).

    Association of Keyboarding Fluency and Writing Performance in Online-Delivered Assessment

    Assessing Writing, 51, 100575

    doi:10.1016/j.asw.2021.100575
  52. james-engelhardt-2012

    James, Karin H.; Engelhardt, Laura (2012).

    The Effects of Handwriting Experience on Functional Brain Development in Pre-Literate Children

    Trends in Neuroscience and Education, 1, (1), 32–42

    doi:10.1016/j.tine.2012.08.001
  53. marano-2025

    Marano, Giuseppe; Kotzalidis, Georgios D.; Lisci, Francesco Maria; et al. (2025).

    The Neuroscience Behind Writing: Handwriting vs. Typing: Who Wins the Battle?

    Life, 15, (3), 345

    doi:10.3390/life15030345
  54. cerni-2025

    Cerni, Tania; Lonciari, Isabella; Job, Remo (2025).

    Learning by Writing: The Influence of Handwriting and Typing on Novel Word Learning in Typically Developing Readers and Readers With Dyslexia

    Learning and Instruction, 98, 102119

    doi:10.1016/j.learninstruc.2025.102119
  55. glimcher-2011

    Glimcher, Paul W. (2011).

    Understanding Dopamine and Reinforcement Learning: The Dopamine Reward Prediction Error Hypothesis

    Proceedings of the National Academy of Sciences, 108, 15647–15654

    doi:10.1073/pnas.1014269108
  56. zhao-2024

    Zhao, Jingwang; Zhang, Guanghu; Xu, Dongsheng (2024).

    The effect of reward on motor learning: different stage, different effect

    Frontiers in Human Neuroscience, 18, 1381935

    doi:10.3389/fnhum.2024.1381935
  57. nikooyan-ahmed-2015

    Nikooyan, Ali A.; Ahmed, Alaa A. (2015).

    Reward Feedback Accelerates Motor Learning

    Journal of Neurophysiology, 113, (2), 633–646

    doi:10.1152/jn.00032.2014
  58. wood-2021

    Wood, A. N. (2021).

    New roles for dopamine in motor skill acquisition: lessons from primates, rodents, and songbirds

    Journal of Neurophysiology, 125, (6), 2361-2374

    doi:10.1152/jn.00648.2020
  59. phillips-2024

    Phillips, Chris D.; Hodge, Alexander T.; Myers, Courtney C.; Leventhal, Daniel K.; Burgess, Christian R. (2024).

    Striatal Dopamine Contributions to Skilled Motor Learning

    The Journal of Neuroscience, 44, (26), e0240242024

    doi:10.1523/jneurosci.0240-24.2024
  60. hull-2020

    Hull, Courtney (2020).

    Prediction Signals in the Cerebellum: Beyond Supervised Motor Learning

    eLife, 9, e54073

    doi:10.7554/eLife.54073
  61. huvermann-2025

    Huvermann, Dana M.; Berlijn, Adam M.; Thieme, Andreas; et al. (2025).

    The Cerebellum Contributes to Prediction Error Coding in Reinforcement Learning in Humans

    The Journal of Neuroscience, 45, (19), e1972242025

    doi:10.1523/jneurosci.1972-24.2025
  62. hong-2025

    Hong, Huaqing; Dai, Ling; Zheng, Xiulin (2025).

    Advances in Wearable Sensors for Learning Analytics: Trends, Challenges, and Prospects

    Sensors, 25, (9), 2714

    doi:10.3390/s25092714
  63. kim-2024-hrv

    Kim, Hyun Jin; Park, Yuyi; Lee, Jihyun (2024).

    The Validity of Heart Rate Variability (HRV) in Educational Research and a Synthesis of Recommendations

    Educational Psychology Review, 36, 42

    doi:10.1007/s10648-024-09878-x
  64. solhjoo-2019

    Solhjoo, Soroosh; Haigney, Mark C.; McBee, Elexis; et al. (2019).

    Heart Rate and Heart Rate Variability Correlate with Clinical Reasoning Performance and Self-Reported Measures of Cognitive Load

    Scientific Reports, 9, 14668

    doi:10.1038/s41598-019-50280-3
  65. ranti-2020

    Ranti, Carolyn; Jones, Warren; Klin, Ami; Shultz, Sarah (2020).

    Blink Rate Patterns Provide a Reliable Measure of Individual Engagement with Scene Content

    Scientific Reports, 10, 8267

    doi:10.1038/s41598-020-64999-x
  66. magliacano-2020

    Magliacano, A.; Fiorenza, S.; Estraneo, A.; Trojano, L. (2020).

    Eye Blink Rate Increases as a Function of Cognitive Load During an Auditory Oddball Paradigm

    Neuroscience Letters, 736, 135293

    doi:10.1016/j.neulet.2020.135293
  67. coupal-2025

    Coupal, Penelope; Zhang, Yue; Deroche, Mickael (2025).

    Reduced Eye Blinking During Sentence Listening Reflects Increased Cognitive Load in Challenging Auditory Conditions

    Trends in Hearing, 29, 23312165251371118

    doi:10.1177/23312165251371118
  68. alfredo-2024

    Alfredo, R.; Echeverria, V.; Jin, Y.; et al. (2024).

    Human-Centred Learning Analytics and AI in Education: A Systematic Literature Review

    Computers and Education: Artificial Intelligence, 6, 100215

    doi:10.1016/j.caeai.2024.100215
  69. pardo-siemens-2014

    Pardo, Abelardo; Siemens, George (2014).

    Ethical and Privacy Principles for Learning Analytics

    British Journal of Educational Technology, 45, (3), 438–450

    doi:10.1111/bjet.12152
  70. cipriano-2023-sel

    Cipriano, Christina; Strambler, Michael J; Naples, Lauren H; et al. (2023).

    The state of evidence for social and emotional learning: A contemporary meta-analysis of universal school-based SEL interventions

    Child Development, 94, (5), 1181-1204

    doi:10.1111/cdev.13968
  71. maccann-2020-emotional-intelligence

    MacCann, Carolyn; Jiang, Yixin; Brown, Luke E. R.; Double, Kit S.; Bucich, Micaela; Minbashian, Amirali (2020).

    Emotional intelligence predicts academic performance: A meta-analysis.

    Psychological Bulletin, 146, (2), 150-186

    doi:10.1037/bul0000219
  72. vaughan-2026-service-learning

    Vaughan, Ashley K.; Carbonneau, Kira J. (2026).

    A Meta-Analysis of Collegiate Service-Learning Teaching Strategies

    Journal of the Scholarship of Teaching and Learning, 26, (1)

    doi:10.14434/josotl.v26i1.37831
  73. jheng-2023-cultural-capital

    Jheng, Ying-jie; Lin, Chun-wen; Liao, Yuen-kuang (2023).

    The way cultural capital works: A meta-analysis of the effects of cultural capital on student's reading performance

    International Journal of Educational Research, 122, 102259

    doi:10.1016/j.ijer.2023.102259
  74. erickson-2024-field-trips

    Erickson, Heidi H.; Watson, Angela R.; Greene, Jay P. (2024).

    An Experimental Evaluation of Culturally Enriching Field Trips

    Journal of Human Resources, 59, (3), 879-904

    doi:10.3368/jhr.1020-11242r1
  75. yu-2025-blended-learning

    Yu, Qing; Yu, Kun; Li, Baomin; Wang, Qiyun (2025).

    Effectiveness of blended learning on students’ learning performance: a meta-analysis

    Journal of Research on Technology in Education, 57, (3), 499-520

    doi:10.1080/15391523.2023.2264984
  76. jamey-2024-music-inhibition

    Jamey, Kevin; Foster, Nicholas E.V.; Hyde, Krista L.; Dalla Bella, Simone (2024).

    Does music training improve inhibition control in children? A systematic review and meta-analysis

    Cognition, 252, 105913

    doi:10.1016/j.cognition.2024.105913
  77. schellenberg-lima-2024-music-transfer

    Schellenberg, E. Glenn; Lima, César F. (2024).

    Music Training and Nonmusical Abilities

    Annual Review of Psychology, 75, (1), 87-128

    doi:10.1146/annurev-psych-032323-051354
  78. yurtsever-2023-bilingual-executive

    Yurtsever, Asli; Anderson, John A.E.; Grundy, John G. (2023).

    Bilingual children outperform monolingual children on executive function tasks far more often than chance: An updated quantitative analysis

    Developmental Review, 69, 101084

    doi:10.1016/j.dr.2023.101084
  79. lowe-2021-bilingual-executive

    Lowe, Cassandra J.; Cho, Isu; Goldsmith, Samantha F.; Morton, J. Bruce (2021).

    The Bilingual Advantage in Children’s Executive Functioning Is Not Related to Language Status: A Meta-Analytic Review

    Psychological Science, 32, (7), 1115-1146

    doi:10.1177/0956797621993108
  80. wang-wei-2024-parental-math

    Wang, Xueshen; Wei, Yun (2024).

    The influence of parental involvement on students’ math performance: a meta-analysis

    Frontiers in Psychology, 15, 1463359

    doi:10.3389/fpsyg.2024.1463359
  81. xu-2024-parental-homework

    Xu, Jianzhong; Guo, Shengli; Feng, Yuxiang; et al. (2024).

    Parental Homework Involvement and Students’ Achievement: A Three-Level Meta-Analysis

    Psicothema, 36, (1), 1-14

    doi:10.7334/psicothema2023.92
  82. blume-2010-training-transfer

    Blume, Brian D.; Ford, J. Kevin; Baldwin, Timothy T.; Huang, Jason L. (2010).

    Transfer of Training: A Meta-Analytic Review

    Journal of Management, 36, (4), 1065-1105

    doi:10.1177/0149206309352880
  83. chirikov-2020-online-stem

    Chirikov, Igor; Semenova, Tatiana; Maloshonok, Natalia; Bettinger, Eric; Kizilcec, René F. (2020).

    Online education platforms scale college STEM instruction with equivalent learning outcomes at lower cost

    Science Advances, 6, (15), eaay5324

    doi:10.1126/sciadv.aay5324
  84. caird-2015-teaching-carbon

    Caird, Sally; Lane, Andy; Swithenby, Ed; Roy, Robin; Potter, Stephen (2015).

    Design of higher education teaching models and carbon impacts

    International Journal of Sustainability in Higher Education, 16, (1), 96-111

    doi:10.1108/ijshe-06-2013-0065
  85. emslander-2025-relationships

    Emslander, Valentin; Holzberger, Doris; Ofstad, Sverre Berg; Fischbach, Antoine; Scherer, Ronny (2025).

    Teacher–student relationships and student outcomes: A systematic second-order meta-analytic review

    Psychological Bulletin, 151, (3), 365-397

    doi:10.1037/bul0000461
  86. raposa-2019-mentoring

    Raposa, Elizabeth B.; Rhodes, Jean; Stams, Geert Jan J. M.; et al. (2019).

    The Effects of Youth Mentoring Programs: A Meta-analysis of Outcome Studies

    Journal of Youth and Adolescence, 48, (3), 423-443

    doi:10.1007/s10964-019-00982-8
  87. jackson-mackevicius-2024-spending

    Jackson, C. Kirabo; Mackevicius, Claire L. (2024).

    What Impacts Can We Expect from School Spending Policy? Evidence from Evaluations in the United States

    American Economic Journal: Applied Economics, 16, (1), 412-446

    doi:10.1257/app.20220279
  88. cantoni-2017-curriculum

    Cantoni, Davide; Chen, Yuyu; Yang, David Y.; Yuchtman, Noam; Zhang, Y. Jane (2017).

    Curriculum and Ideology

    Journal of Political Economy, 125, (2), 338-392

    doi:10.1086/690951
  89. glewwe-2009-textbooks

    Glewwe, Paul; Kremer, Michael; Moulin, Sylvie (2009).

    Many Children Left Behind? Textbooks and Test Scores in Kenya

    American Economic Journal: Applied Economics, 1, (1), 112-135

    doi:10.1257/app.1.1.112
  90. wineburg-2022-lateral-reading

    Wineburg, Sam; Breakstone, Joel; McGrew, Sarah; Smith, Mark D.; Ortega, Teresa (2022).

    Lateral reading on the open Internet: A district-wide field study in high school government classes

    Journal of Educational Psychology, 114, (5), 893-909

    doi:10.1037/edu0000740
  91. may-2024-reading-recovery

    May, Henry; Blakeney, Aly; Shrestha, Pragya; Mazal, Mia; Kennedy, Nicole (2024).

    Long-Term Impacts of Reading Recovery through 3rd and 4th Grade: A Regression Discontinuity Study

    Journal of Research on Educational Effectiveness, 17, (3), 433-458

    doi:10.1080/19345747.2023.2209092
  92. roy-2024-chatgpt-planning

    Roy, Palak; Poet, Helen; Staunton, Ruth; Aston, Katherine; Thomas, David (2024).

    ChatGPT in Lesson Preparation: A Teacher Choices Trial

    Education Endowment Foundation, Evaluation report

    View authoritative source
  93. oecd-talis-2025

    OECD (2025).

    Results from TALIS 2024: The State of Teaching

    OECD Publishing

    doi:10.1787/90df6235-en
  94. lyon-2026-strikes

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