A revision of bloom's taxonomy: an overview
Open accessAbstract
(2002). A Revision of Bloom's Taxonomy: An Overview. Theory Into Practice: Vol. 41, Revising Bloom's Taxonomy, pp. 212-218.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The text we found for this paper looks like another document, so the self-check wasn’t run.
Cites
(2001) · Cited by 13,930 · see citing works
Self-citationBloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956) · Cited by 9,342 · see citing works
Self-citation(1956) · Medical Entomology and Zoology · Cited by 4,596 · see citing works
Self-citationAnderson, L. W., & Krathwohl, D. R. (2001) · Bibliothèque et Archives nationales du Québec (Québec government) · Cited by 1,194 · see citing works
Self-citationTHE CLASSIFICATION OF EDUCATIONAL OBJECTIVES, PSYCHOMOTOR DOMAIN.
Simpson, E. J. (1966) · Cited by 640 · see citing works
A Taxonomy of the Psychomotor Domain: A Guide for Developing Behavioral Objectives
Cooper, W. F., & Harrow, A. J. (1973) · American Educational Research Journal · doi:10.2307/1161665 · Cited by 345 · see citing works
Airasian, P. W. (2000) · Cited by 63 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- Dave, R.H. (1970). Psychomotor levels. In R.J. Armstrong (Ed.), Developing and writing educational objectives (pp. 33-34). Tucson AZ: Educational Innovators Press.
- Simpson B.J., 1966, Illinois Journal of Home Economics, 10, 110
Cited by
Sorted by citations
Social robots for education: a review.
Belpaeme, T., Kennedy, J., Ramachandran, A., Scassellati, B., & Tanaka, F. (2018) · Science Robotics · doi:10.1126/scirobotics.aat5954 · Cited by 1,558 · see citing works
Enhancing Student Engagement Using the Flipped Classroom
Gilboy, M. B., Heinerichs, S., & Pazzaglia, G. (2014) · Journal of Nutrition Education and Behavior · doi:10.1016/j.jneb.2014.08.008 · Cited by 1,120 · see citing works
Increased Structure and Active Learning Reduce the Achievement Gap in Introductory Biology
Haak, D. C., HilleRisLambers, J., Pitre, E., & Freeman, S. (2011) · Science · doi:10.1126/science.1204820 · Cited by 959 · see citing works
Handbook of Research on Learning and Instruction
Mayer, R., Alexander, P., & Fiorella, L. (2011) · Routledge eBooks · doi:10.4324/9780203839089 · Cited by 323 · see citing works
An integrated critical thinking framework for the 21st century
Dwyer, C. P., Hogan, M., & Stewart, I. (2014) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2013.12.004 · Cited by 861 · see citing works
The essential elements of team‐based learning
Michaelsen, L. K., & Sweet, M. (2008) · New Directions for Teaching and Learning · doi:10.1002/tl.330 · Cited by 846 · see citing works
Fan, Y., Tang, L., Le, H., Shen, K., Tan, S., Zhao, Y., Shen, Y., Li, X., & Gašević, D. (2025) · British Journal of Educational Technology · doi:10.1111/bjet.13544 · Cited by 805 · see citing works
Hamilton, E. R., Rosenberg, J. M., & Akcaoğlu, M. (2016) · TechTrends · doi:10.1007/s11528-016-0091-y · Cited by 690 · see citing works
Chen, Y., Jensen, S., Albert, L. J., Gupta, S., & Lee, T. (2023) · Information Systems Frontiers · doi:10.1007/s10796-022-10291-4 · Cited by 685 · see citing works
An effective blended online teaching and learning strategy during the COVID-19 pandemic
Lapitan, L. D., Tiangco, C. E., Sumalinog, D. A. G., Sabarillo, N. S., & Diaz, J. M. S. (2021) · Education for Chemical Engineers · doi:10.1016/j.ece.2021.01.012 · Cited by 628 · see citing works
Kononowicz, A. A., Woodham, L. A., Edelbring, S., Stathakarou, N., Davies, D., Saxena, N., Tudor Car, L., Carlstedt-Duke, J., Car, J., & Zary, N. (2019) · Journal of Medical Internet Research · doi:10.2196/14676 · Cited by 600 · see citing works
Archer, D. R., Adu-Gyamfi, J., & Goyal, A. (2002) · Cited by 596 · see citing works
The flipped classroom: for active, effective and increased learning – especially for low achievers
Nouri, J. (2016) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-016-0032-z · Cited by 535 · see citing works
Relationships Between Game Attributes and Learning Outcomes: Review and Research Proposals
Wilson, K. A., Bedwell, W. L., Lazzara, E. H., Salas, E., Burke, C. S., Estock, J. L., Orvis, K. L., & Conkey, C. (2009) · Simulation & Gaming · doi:10.1177/1046878108321866 · Cited by 524 · see citing works
Cheng, L., Ritzhaupt, A. D., & Antonenko, P. (2019) · Educational Technology Research and Development · doi:10.1007/s11423-018-9633-7 · Cited by 494 · see citing works
The Eras and Trends of Automatic Short Answer Grading
Burrows, S., Gurevych, I., & Stein, B. (2014) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-014-0026-8 · Cited by 480 · see citing works
Marcheti, A. P. D. C., & Belhot, R. V. (2010) · Gestão & Produção · doi:10.1590/s0104-530x2010000200015 · Cited by 443 · see citing works
The role of metacognitive skills in developing critical thinking
Magno, C. (2010) · Metacognition and Learning · doi:10.1007/s11409-010-9054-4 · Cited by 443 · see citing works
Writing and using learning outcomes: a practical guide
Kennedy, D. (2006) · Cork Open Research Archive (University College Cork, Ireland) · Cited by 440 · see citing works
Baartman, L. K. J., & de Bruijn, E. (2011) · Educational Research Review · doi:10.1016/j.edurev.2011.03.001 · Cited by 436 · see citing works
Emotional presence, learning, and the online learning environment
Cleveland-Innes, M. F., & Campbell, P. (2012) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v13i4.1234 · Cited by 419 · see citing works
Generative Artificial Intelligence: Implications and Considerations for Higher Education Practice
Farrelly, T., & Baker, N. (2023) · Education Sciences · doi:10.3390/educsci13111109 · Cited by 414 · see citing works
“Specifically, instead of aligning with the original 1956 Taxonomy, we suggest that Bloom’s Revised Taxonomy [51] is a more suitable match in this instance.”
MethodDoes animation enhance learning? A meta-analysis
Berney, S., & Bétrancourt, M. (2016) · Computers & Education · doi:10.1016/j.compedu.2016.06.005 · Cited by 378 · see citing works
Chang, D. H., Lin, M. P.-C., Hajian, S., & Wang, Q. Q. (2023) · Sustainability · doi:10.3390/su151712921 · Cited by 370 · see citing works
“To better understand this, we can break prompts down into two types: cognitive prompts and metacognitive prompts, by drawing on Bloom’s Taxonomy [62].”
MethodCommonly known, commonly not known, totally unknown: a framework for students becoming researchers
Willison, J., & O’Regan, K. (2007) · Higher Education Research & Development · doi:10.1080/07294360701658609 · Cited by 367 · see citing works
Revisi taksonomi Bloom: Kognitif, afektif, dan psikomotorik
Nafiati, D. A. (2021) · HUMANIKA · doi:10.21831/hum.v21i2.29252 · Cited by 364 · see citing works
Learning computer science concepts with Scratch
Meerbaum–Salant, O., Armoni, M., & Ben‐Ari, M. (2013) · Computer Science Education · doi:10.1080/08993408.2013.832022 · Cited by 360 · see citing works
Dependency and coürdination in the grammar of Dutch and English
Steedman, M. J. (1985) · Language · doi:10.2307/414385 · Cited by 354 · see citing works
Integrated STEM defined: Contexts, challenges, and the future
Nadelson, L. S., & Seifert, A. L. (2017) · The Journal of Educational Research · doi:10.1080/00220671.2017.1289775 · Cited by 347 · see citing works
BLOOM'S TAXONOMY: ORIGINAL AND REVISED
Oscarini, S. L., & Bhakti, W. (2010) · Cited by 338 · see citing works
The role of self-regulated learning in students' success in flipped undergraduate math courses
Sun, Z., Xie, K., & Anderman, L. H. (2017) · The Internet and Higher Education · doi:10.1016/j.iheduc.2017.09.003 · Cited by 326 · see citing works
Jensen, J. L., McDaniel, M. A., Woodard, S. M., & Kummer, T. A. (2014) · Educational Psychology Review · doi:10.1007/s10648-013-9248-9 · Cited by 324 · see citing works
Emerging Perspectives on Learning, teaching, and technology
Orey, M. A. (2001) · Cited by 323 · see citing works
Olsson, D., Gericke, N., & Rundgren, S.-N. C. (2015) · Environmental Education Research · doi:10.1080/13504622.2015.1005057 · Cited by 315 · see citing works
Loyens, S. M. M., van Meerten, J. E., Schaap, L., & Wijnia, L. (2023) · Educational Psychology Review · doi:10.1007/s10648-023-09757-x · Cited by 307 · see citing works
Increased Course Structure Improves Performance in Introductory Biology
Freeman, S., Haak, D., & Wenderoth, M. P. (2011) · CBE—Life Sciences Education · doi:10.1187/cbe.10-08-0105 · Cited by 306 · see citing works
An integrated approach to BIM competency assessment, acquisition and application
Succar, B., Sher, W., & Williams, A. P. (2013) · Automation in Construction · doi:10.1016/j.autcon.2013.05.016 · Cited by 303 · see citing works
Zhao, W., He, L., Deng, W., Zhu, J., Su, A., & Zhang, Y. (2020) · BMC Medical Education · doi:10.1186/s12909-020-02306-y · Cited by 295 · see citing works
Just the Facts? Introductory Undergraduate Biology Courses Focus on Low-Level Cognitive Skills
Momsen, J. L., Long, T. M., Wyse, S. A., & Ebert‐May, D. (2010) · CBE—Life Sciences Education · doi:10.1187/cbe.10-01-0001 · Cited by 290 · see citing works
Wekerle, C., Daumiller, M. H., & Kollar, I. (2020) · Journal of Research on Technology in Education · doi:10.1080/15391523.2020.1799455 · Cited by 290 · see citing works
Developing a computer science-specific learning taxonomy
Fuller, U., Johnson, C. G., Ahoniemi, T., Cukierman, D., Losada, I. H., Jacková, J., Lahtinen, E., Lewis, T. L., Thompson, D. M., Riedesel, C. P., et al. (2007) · ACM SIGCSE Bulletin · doi:10.1145/1345375.1345438 · Cited by 283 · see citing works
Lee, H.-Y., Chen, P.-H., Wang, W.-S., Huang, Y.-M., & Wu, T.-T. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00447-4 · Cited by 273 · see citing works
“This level of scrutiny encourages learners to not just passively accept information but to actively engage in questioning and appraising its validity and utility (Krathwohl, 2002).”
BackgroundDalton‐Puffer, C. (2013) · European Journal of Applied Linguistics · doi:10.1515/eujal-2013-0011 · Cited by 273 · see citing works
Sohrabi, B., & Iraj, H. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.02.056 · Cited by 269 · see citing works
Frameworks for learner assessment in medicine: AMEE Guide No. 78
Pangaro, L. N., & ten Cate, O. (2013) · Medical Teacher · doi:10.3109/0142159x.2013.788789 · Cited by 267 · see citing works
Oh, P. J., Jeon, K. D., & Koh, M. S. (2015) · Nurse Education Today · doi:10.1016/j.nedt.2015.01.019 · Cited by 262 · see citing works
Gamification for student engagement: a framework
Rivera, E. S., & Garden, C. L. P. (2021) · Journal of Further and Higher Education · doi:10.1080/0309877x.2021.1875201 · Cited by 256 · see citing works
The influence of AI text generators on critical thinking skills in UK business schools
Essien, A., Bukoye, O. T., O’Dea, X., & Kremantzis, M. (2024) · Studies in Higher Education · doi:10.1080/03075079.2024.2316881 · Cited by 252 · see citing works
A Framework for the Use of Immersive Virtual Reality in Learning Environments
Mulders, M., Buchner, J., & Kerres, M. (2020) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v15i24.16615 · Cited by 252 · see citing works
Critical thinking in the preschool classroom - A systematic literature review
O'Reilly, C., Devitt, A., & Hayes, N. (2022) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2022.101110 · Cited by 251 · see citing works
Student Motivation from and Resistance to Active Learning Rooted in Essential Science Practices
Owens, D., Sadler, T. D., Barlow, A. T., & Smith-Walters, C. (2017) · Research in Science Education · doi:10.1007/s11165-017-9688-1 · Cited by 235 · see citing works
Declarative knowledge acquisition in immersive virtual learning environments
Webster, R. (2016) · Interactive Learning Environments · doi:10.1080/10494820.2014.994533 · Cited by 233 · see citing works
Nikou, S. A., & Economides, A. A. (2018) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12240 · Cited by 229 · see citing works
From Emerging Perspectives on Learning, Teaching and Technology
Kim, B. (2006) · Cited by 226 · see citing works
Kim, N. J., Belland, B. R., & Walker, A. E. (2018) · Educational Psychology Review · doi:10.1007/s10648-017-9419-1 · Cited by 220 · see citing works
Learning computer science concepts with scratch
Meerbaum–Salant, O., Armoni, M., & Ben‐Ari, M. (2010) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/1839594.1839607 · Cited by 217 · see citing works
Jeronen, E. K., Palmberg, I., & Yli‐Panula, E. (2016) · Education Sciences · doi:10.3390/educsci7010001 · Cited by 217 · see citing works
Learning Analytics in Higher Education
Lester, J., Klein, C., Rangwala, H., & Johri, A. (2017) · ASHE Higher Education Report · doi:10.1002/aehe.20121 · Cited by 217 · see citing works
Digital transformation and hospitality management competencies: Toward an integrative framework
Busulwa, R., Pickering, M. E., & Mao, I. (2021) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2021.103132 · Cited by 212 · see citing works
Teaching about Climate Change in Medical Education: An Opportunity
Maxwell, J., & Blashki, G. A. (2016) · Journal of Public Health Research · doi:10.4081/jphr.2016.673 · Cited by 211 · see citing works
Tolsgaard, M. G., Todsen, T., Sørensen, J. L., Ringsted, C. V., Lorentzen, T., Ottesen, B., & Tabor, A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057687 · Cited by 208 · see citing works
Robot education peers in a situated primary school study: Personalisation promotes child learning
Baxter, P. E., Ashurst, E. J., Read, R., Kennedy, J., & Belpaeme, T. (2017) · PLoS ONE · doi:10.1371/journal.pone.0178126 · Cited by 207 · see citing works
Birgili, B., Seggie, F. N., & Oğuz, E. (2021) · Journal of Computers in Education · doi:10.1007/s40692-021-00183-y · Cited by 207 · see citing works
Workforce Framework for Cybersecurity (NICE Framework)
Petersen, R. J., dos Santos, D. M. D. S. S., Smith, M. C., Wetzel, K. A., & Witte, G. (2020) · doi:10.6028/nist.sp.800-181r1 · Cited by 206 · see citing works
Digital Literacy: A Prerequisite for Effective Learning in a Blended Learning Environment?.
Tang, C. M., & Chaw, L. Y. (2016) · The Electronic Journal of e-Learning · Cited by 205 · see citing works
The Effects of Virtual Reality Learning Environment on Student Cognitive and Linguistic Development
Chen, Y.-L. (2016) · The Asia-Pacific Education Researcher · doi:10.1007/s40299-016-0293-2 · Cited by 200 · see citing works
Maindal, H. T., Kayser, L., Norgaard, O., Bo, A., Elsworth, G. R., & Osborne, R. H. (2016) · SpringerPlus · doi:10.1186/s40064-016-2887-9 · Cited by 200 · see citing works
Multiple‐Choice Tests and Student Understanding: What Is the Connection?
Simkin, M. G., & Kuechler, W. L. (2005) · Decision Sciences Journal of Innovative Education · doi:10.1111/j.1540-4609.2005.00053.x · Cited by 199 · see citing works
MOOC Pedagogy: Gleaning Good Practice from Existing MOOCs
Bali, M. (2014) · Cited by 198 · see citing works
State of the App: A Taxonomy and Framework for Evaluating Language Learning Mobile Applications
Rosell-Aguilar, F. (2017) · CALICO Journal · doi:10.1558/cj.27623 · Cited by 196 · see citing works
Din, M. (2020) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2020.100627 · Cited by 193 · see citing works
Using Bloom’s Taxonomy to teach sustainability in multiple contexts
Pappas, E. C., Pierrakos, O., & Nagel, R. (2012) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2012.09.039 · Cited by 192 · see citing works
Is using ChatGPT cheating, plagiarism, both, neither, or forward thinking?
Anders, B. A. (2023) · Patterns · doi:10.1016/j.patter.2023.100694 · Cited by 192 · see citing works
Searching as learning: A systematization based on literature
Vakkari, P. (2016) · Journal of Information Science · doi:10.1177/0165551515615833 · Cited by 189 · see citing works
A Framework for Characterizing eHealth Literacy Demands and Barriers
Chan, C., & Kaufman, D. R. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1750 · Cited by 189 · see citing works
The role of textbook learning resources in e-learning: A taxonomic study
Lau, K. H., Lam, T. K., Kam, B., Nkhoma, M. Z., Richardson, J., & Thomas, S. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.11.005 · Cited by 188 · see citing works
From problem-based learning to practice-based education: a framework for shaping future engineers
Mann, L. M. W., Chang, R., Chandrasekaran, S., Coddington, A., Daniel, S., Cook, E. J., Crossin, E., Cosson, B., Turner, J., Mazzurco, A., et al. (2020) · European Journal of Engineering Education · doi:10.1080/03043797.2019.1708867 · Cited by 186 · see citing works
Kolenatý, M., Kroufek, R., & Činčera, J. (2022) · Sustainability · doi:10.3390/su141610365 · Cited by 186 · see citing works
Flynn, A. B. (2014) · Chemistry Education Research and Practice · doi:10.1039/c4rp00224e · Cited by 183 · see citing works
Novice Programmers and Introductory Programming
Robins, A. V. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.013 · Cited by 183 · see citing works
Bellaera, L., Weinstein-Jones, Y., Ilie, S., & Baker, S. T. (2021) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2021.100856 · Cited by 182 · see citing works
Lee, H., Parsons, D., Kwon, G. H., Kim, J., Petrova, K., Jeong, E., & Ryu, H. B. (2016) · Computers & Education · doi:10.1016/j.compedu.2016.03.006 · Cited by 182 · see citing works
Does “flipping” promote engagement?: A comparison of a traditional, online, and flipped class
Burke, A. S., & Fedorek, B. (2017) · Active Learning in Higher Education · doi:10.1177/1469787417693487 · Cited by 180 · see citing works
Embodied interactive video lectures for improving learning comprehension and retention
Hung, I., Kinshuk, K., & Chen, N. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.10.005 · Cited by 180 · see citing works
Human and AI collaboration in the higher education environment: opportunities and concerns
Atchley, P., Pannell, H., Wofford, K., Hopkins, M., & Atchley, R. A. (2024) · Cognitive Research Principles and Implications · doi:10.1186/s41235-024-00547-9 · Cited by 180 · see citing works
Critical thinking, questioning and student engagement in Korean university English courses
DeWaelsche, S. A. (2015) · Linguistics and Education · doi:10.1016/j.linged.2015.10.003 · Cited by 178 · see citing works
Jo, İ., & Bednarz, S. W. (2009) · Journal of Geography · doi:10.1080/00221340902758401 · Cited by 177 · see citing works
Keep it Coherent: A Meta-Analysis of the Seductive Details Effect
Sundararajan, N., & Adesope, O. (2020) · Educational Psychology Review · doi:10.1007/s10648-020-09522-4 · Cited by 176 · see citing works
Tittel, A., & Terzidis, O. (2020) · Entrepreneurship Education · doi:10.1007/s41959-019-00021-4 · Cited by 175 · see citing works
Johnson, T. E., Archibald, T. N., & Tenenbaum, G. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.05.014 · Cited by 171 · see citing works
Students’ creative thinking process stages: Implementation of realistic mathematics education
Sitorus, J., & Masrayati (2016) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2016.09.007 · Cited by 170 · see citing works
Ragan, E. D. (2010) · PRESENCE Virtual and Augmented Reality · doi:10.1162/pres_a_00016 · Cited by 166 · see citing works
Falloon, G. (2016) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12155 · Cited by 166 · see citing works
In-service teachers’ (mis)conceptions of artificial intelligence in K-12 science education
Antonenko, P., & Abramowitz, B. (2022) · Journal of Research on Technology in Education · doi:10.1080/15391523.2022.2119450 · Cited by 166 · see citing works
Bowman, M. A., Vongkulluksn, V. W., Jiang, Z., & Xie, K. (2020) · Journal of Research on Technology in Education · doi:10.1080/15391523.2020.1830895 · Cited by 163 · see citing works
Khan, K., & Ramachandran, S. (2012) · Medical Teacher · doi:10.3109/0142159x.2012.722707 · Cited by 162 · see citing works
Heo, M., & Toomey, N. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.103747 · Cited by 162 · see citing works
Generative AI’s Impact on Critical Thinking: Revisiting Bloom’s Taxonomy
Gonsalves, C. (2026) · Journal of Marketing Education · doi:10.1177/02734753241305980 · Cited by 161 · see citing works
Talley, C. P., & Scherer, S. (2013) · The Journal of Negro Education · doi:10.7709/jnegroeducation.82.3.0339 · Cited by 161 · see citing works
ChatGPT for design, manufacturing, and education
Wang, X., Anwer, N., Dai, Y., & Liu, A. (2023) · Procedia CIRP · doi:10.1016/j.procir.2023.04.001 · Cited by 157 · see citing works
- Authors
- Krathwohl, D. R.
- Corresponding author
- Krathwohl, David R.
- Venue
- Theory Into Practice
- Publisher
- Informa UK Limited
- Published
- 2002-11-01
- Volume
- 41
- Issue
- 4
- Pages
- 212-218
- ISSN
- 0040-5841 (ISSN-L)
- 1543-0421
- OpenAlex
- W2162821268
- Semantic Scholar
- 93c7232b15a84f2d37a5184a65d13a22fc15df31
- Cited by
- 8,132
- References
- 7
- Citations by year
- 2026: 717 · 2025: 694 · 2024: 657 · 2023: 678 · 2022: 631 · 2021: 660 · 2020: 636 · 2019: 541 · 2018: 405 · 2017: 478 · 2016: 393 · 2015: 396 · 2014: 353 · 2013: 280 · 2012: 197
- FWCI
- 50.42
- Type
- journal article
- Language
- en
- Open access
- green
- dergipark.org.tr
- Locations
- Theory Into Practice (publishedVersion)
- DergiPark (Istanbul University) (submittedVersion)
- İlköğretim Online (elektronik)
- Topics
- Social Sciences › Education › Educational Assessment and Pedagogy
- Social Sciences › Education › Education and Critical Thinking Development
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Keywords
- Bloom's taxonomy, Bloom's revised taxonomy, educational objectives, learning outcomes
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review