Los juicios metacognitivos como un campo emergente de investigación. Una revisión sistemática (2016-2020)
Titulo:

Los juicios metacognitivos como un campo emergente de investigación. Una revisión sistemática (2016-2020)
.

Sumario:

Objetivo: establecer las tendencias conceptuales en la investigación sobre juicios metacognitivos en estudiantes universitarios. Método: se desarrolló una búsqueda en las bases de datos Web of Science y Scopus en el período 2016-2020 para artículos publicados en idioma inglés, atendiendo a la metodología de revisión sistemática. Una vez aplicados los criterios de depuración a la base de datos, se procedió a realizar los análisis descriptivos derivados. Resultados: se analizaron 21 artículos que cumplieron con los criterios de inclusión. Se encontraron 6 tendencias conceptuales entre las que se evidenció una importante orientación del campo hacia los estudios de monitoreo metacognitivo, además, de algunas nuevas tendencias que empiezan a eme... Ver más

Guardado en:

Latinoamericana de Estudios Educativos

1900-9895

2500-5324

Tamayo Alzate, Óscar Eugenio

Puente Ferreras, Aníbal

Orrego Cardozo, Mary

Montoya Londoño, Diana Marcela

UNIVERSIDAD DE CALDAS

10.17151/rlee.2021.17.1.10

17

2020-01-01

188

223

Colombia

autoeficacia

procesos cognitivos

aprendizaje

metamemoria

metacognición

http://purl.org/coar/access_right/c_abf2

info:eu-repo/semantics/openAccess

id oai:revistasojs.ucaldas.edu.co:article-4273
record_format ojs
spelling Los juicios metacognitivos como un campo emergente de investigación. Una revisión sistemática (2016-2020)
Metcalfe, J., & Kornell, N. (2005). A Region of Proximal Learning model of study time allocation. Journal of Memory and Language, 52 (4), 463-477. https://doi.org/10.1016/j.jml.2004.12.001
Pieger, E., Mengelkamp, C., & Bannert, M. (2017). Fostering Analytic Metacognitive Processes and Reducing Overconfidence by Disfluency: The Role of Contrast Effects. Applied Cognitive Psychology, 31 (3), 291-301. https://doi.org/10.1002/acp.3326
Petticrew, M., & Roberts, H. (2008). Systematic Reviews in the social sciences. New York: John Wiley y Sons, Ltd.
Paris, S., & Byrnes, J. (1989). The constructivist approach to self-regulation and learning in the classroom. In Zimmerman, B.& Schunk, D. (Eds.), Self -regulated learning and academic achievement (pp. 169-200). New York: Springer- Verlag.
Panadero, E., Broadbent, J., Boud, D., & Lodge, J. M. (2019). Using formative assessment to influence self- and co-regulated learning: the role of evaluative judgement. European Journal of Psychology of Education, 34 (3), 535-557. https://doi.org/10.1007/s10212-018-0407-8
Nelson, T. (1984). A comparison of current measures of the accuracy of feeling of knowing predictions. Psychological Bulletin, 95 (1), 109-133.
Nelson, T., & Narens, L. (1994). Why investigate metacognitive? In Metcalfe, J. & Shimamura, A. (Eds.), Metacognition: Knowing about knowing (pp. 1-25). United States of America.: The MIT Press Cambridge,.
Nelson, T. O., & Narens, L. (2000). Metamemory: A theoretical framework and new findings. The Psychology of Learning and Motivation, 26. https://doi.org/10.1016/S0079- 7421(08)60053-5
Nelson, T. O., & Leonesio, J. (1988). Allocation of Self-Paced Study Time and the “Laborin-Vain Effect”, 14 (4), 676-686.
Nelson, T. O. (1996). Gamma is a measure of the accuracy of predicting performance on one item relative to another item, not of the absolute performance on an individual item: Comments on schraw (1995). Applied Cognitive Psychology, 10 (3), 257-260. https://doi.org/10.1002/(SICI)1099-0720(199606)10:3<257::AID-ACP400>3.0.CO;2-9
Nelson, T. O. (1992). Metacognition: Core readings. Boston: Allyn and Bacon.
Moshman, D. (1979). To really get ahead, get a metatheory. In Kuhn, D. (Ed.), Intellectual development beyond childhood (pp. 59-68). United States of America: Jossey - Bass.
Morphew, J. W. (2020). Changes in metacognitive monitoring accuracy in an introductory physics course. Metacognition and Learning, 1-23. https://doi.org/10.1007/s11409-020-09239-3
Morphew, J. (2020). Changes in metacognitive monitoring accuracy in an introductory physics course. Metacognition and Learning. https://doi.org/10.1007/s11409-020-09239-3
McNamara, D. S. (2011). Measuring deep, reflective comprehension and learning strategies: Challenges and successes. Metacognition and Learning, 6 (2), 195-203. https://doi.org/10.1007/s11409-011-9082-8
Proust, J. (2010). Metacognition. Philosophy Compass, 11, 989-998.
McCutcheon, G. (1982). Facilitating teacher personal theorizing. In Ross, E., Cornett, & McCutcheon, G. (Eds.), Teacher personal theorizing: connecting curriculum practice, theory and research. New York: Albany, NY.
Mazancieux, A., Fleming, S., Souchay, C., & Moulin, C. (2020). Is there a G factor for metacognition? Correlations in retrospective metacognitive sensitivity across tasks. Journal of Experimental Psychology: General, 149 (9), 1788-1799. https://doi.org/10.1037/xge0000746
Kuhn, D. (1989). Children and adults as intuitive scientist. Psychol. Rev, 96, 674-689. Liberali, J. M., Reyna, V. F., Furlan, S., Stein, L. M., & Pardo, S. T. (2012). Individual Differences in Numeracy and Cognitive Reflection, with Implications for Biases and Fallacies in Probability Judgment. Journal of behavioral decision making, 25 (4, SI), 361-381. https://doi.org/10.1002/bdm.752
Kruger, J., & Dunning, D. (1999). Personality and Social Psychology Unskilled and Unaware of It : How Difficulties in Recognizing One’s Own Incompetence Lead to Inflated. Journal of Personality and Social Psychology, 77 (6), 1121-1134. https://doi.org/10.1037/0022-3514.77.6.1121
Koriat, A., Lichtenstein, S., & Fischhoff, B. (1980). Reasons for confidence. Journal of Experimental Psychology: Human Learning and Memory, 6 (2), 107-118.
Koriat, A. (1997). Monitoring One’s Own Knowledge During Study : A Cue-Utilization Approach to Judgments of Learning. Journal of Experimental Psychology: General, 126 (4), 349-370.
Kollmer, J., Schleinschok, K., Scheiter, K., & Eitel, A. (2020). Is drawing after learning effective for metacognitive monitoring only when supported by spatial scaffolds? Instructional Science, 48 (5), 569-589. https://doi.org/10.1007/s11251-020-09521-6
Higgins, J., & Green, S. (2008). Cochrane handbook for sytematic reviews of interventions. United States of America.: Wiley-Blackwell.
Hawker, M. J., Dysleski, L., & Rickey, D. (2016). Investigating General Chemistry Students Metacognitive Monitoring of Their Exam Performance by Measuring Postdiction Accuracies over Time. Journal of Chemical Education, 93 (5), 832-840. https://doi.org/10.1021/acs.jchemed.5b00705
Hart, J. (1965). Memory and the feeling-of-knowing experience. Journal of educational psychology, 56, 208-216.
Händel, M., Harder, B., & Dresel, M. (2020). Enhanced monitoring accuracy and test performance: Incremental effects of judgment training over and above repeated testing. Learning and Instruction, 65 (November 2018). https://doi.org/10.1016/j.learninstruc.2019.101245
Händel, M., & Fritzsche, E. S. (2016). Unskilled but subjectively aware: Metacognitive monitoring ability and respective awareness in low-performing students. Memory and Cognition, 44 (2), 1-13. https://doi.org/10.3758/s13421-015-0552-0
Händel, M., de Bruin, A. B. H., & Dresel, M. (2020). Individual differences in local and global metacognitive judgments. Metacognition and Learning, 15 (1), 51-75. https://doi.org/10.1007/s11409-020-09220-0
Hacker, D., Dunlosky, J., & Graesser, A. (2009). Handbook of Metacognition in Education. (D. Hacker, J. Dunlosky, & A. Graesser, Eds.). New York: Routledge journals, Taylor & Francis ltd. https://doi.org/10.4324/9780203876428
Pieger, E., Mengelkamp, C., & Bannert, M. (2016). Metacognitive judgments and dis fluency e Does disfluency lead to more accurate judgments, better control, and better performance? Learning and Instruction, 44, 31-40. https://doi.org/10.1016/j.learninstruc.2016.01.012
Quiles, C., Verdoux, H., & Prouteau, A. (2014). Assessing Metacognition during a Cognitive Task: Impact of “On-line” Metacognitive Questions on Neuropsychological Performances in a Non-clinical Sample (March 2015). https://doi.org/10.1017/S1355617714000290
Hacker, D., Bol, L., & Bahbahani, K. (2008). Explaining calibration accuracy in classroom contexts: the effects of incentives, reflection, and explanatory style. Metacognition and Learning, 2, 101-121.
Wagner-Menghin, M., de Bruin, A., van Merrienboer, J. J. G., & van Merriënboer, J. J. G. (2016). Monitoring communication with patients: analyzing judgments of satisfaction (JOS). Advances in Health Sciences Education, 21 (3), 523-540. https://doi.org/10.1007/s10459-015-9642-9
Text
http://purl.org/coar/access_right/c_abf2
info:eu-repo/semantics/openAccess
http://purl.org/coar/version/c_970fb48d4fbd8a85
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:eu-repo/semantics/article
Zimmerman, B., & Moylan, A. (2009). Self -regulation: where metacognition and motivation intersect. In Hacker, D. J., Dunlosky, J. & Grasser, A. (Eds.), Handbook of Metacognition in Education (pp. 239-315). New York: Routledge.
Žauhar, V., Bajšanski, I., & Domijan, D. (2017). The influence of rule availability and item similarity on metacognitive monitoring during categorisation, 5911(November). https://doi.org/10.1080/20445911.2017.1396991
Winne, P., & Muis, K. (2011). Statistical estimates of learners’ judgments about knowledge in calibration of achievement. Metacognition and Learning, 6 (2), 179-193. https://doi.org/10.1007/s11409-011-9074-8
Winne, P., & Azevedo, R. (2014). Metacognition. In K. Sawyer (Ed.), The Cambridge Handbook of the Learning Sciences (pp. 63-87). New York: Cambridge University Press.
Wiley, J., Griffin, T. D., Jaeger, A. J., Jarosz, A. F., Cushen, P. J., & Thiede, K. W. (2016). Improving metacomprehension accuracy in an undergraduate course context. Journal of Experimental Psychology: Applied, 22 (4), 393-405. https://doi.org/10.1037/xap0000096
Wiley, J, Griffin, T., & Thiede, K. (2005). Putting the comprehension in metacomprehension. Journal of General Psychology, 132 (4), 408-428. https://doi.org/10.3200/ GENP.132.4.408-428
Temelman-Yogev, L., Katzir, T., & Prior, A. (2020). Monitoring comprehension in a foreign language: Trait or skill? Metacognition and Learning, 15 (3), 343-365. https://doi.org/10.1007/s11409-020-09245-5
Rhodes, M. G., & Tauber, S. K. (2011). The Influence of Delaying Judgments of Learning on Metacognitive Accuracy: A Meta-Analytic Review. Psychological Bulletin, 137 (1), 131-148. https://doi.org/10.1037/a0021705
Tai, J., Ajjawi, R., Boud, D., Dawson, P., & Panadero, E. (2018). Developing evaluative judgement: enabling students to make decisions about the quality of work. Higher Education, 76 (3), 467-481. https://doi.org/10.1007/s10734-017-0220-3
Segado-Boj, F. (2019). Búsqueda de información bibliográfica para la tesis doctoral Cómo y dónde buscar información para una tesis. Complutense de Madrid. Recuperado de https://eprints.ucm.es/58704/
Schraw, G., & Sperling-Dennison, R. (1994). Assesing metacognitive awareness. Contemporany Educational Psychology, 19, 460-475.
Schraw, G., Kuch, F., Gutierrez, A. P., & Richmond, A. S. (2014). Exploring a three-level model of calibration accuracy. Journal of Educational Psychology, 106 (4). https://doi.org/10.1037/a0036653
Schraw, G., Kuch, F., & Gutierrez, A. P. (2013). Measure for measure : Calibrating ten commonly used calibration scores. Learning and Instruction, 24, 48-57. https://doi.org/10.1016/j.learninstruc.2012.08.007
Schraw, G. (2009b). Measuring metacognitive judgments. In Hacker, D. J., Dunlosky, J. & Graesser, A. (Eds.), Handbook of Metacognition in Education (pp. 415-429). New York: Routledge.
Schraw, G. (2009a). A conceptual analysis of five measures of metacognitive monitoring. Metacognition and Learning, 4 (1), 33-45. https://doi.org/10.1007/s11409-008-9031-3
Schraw, G. (2002). Promoting general metacognitive awareness. In Hartman, H. (Ed.), Metacognition in learning and instruction: Theory, research and practice (pp. 3-16). London: Kluwer Academic.
Schraw, G, Olafson, L., Weibel, M., & Sewing, D. (2012). Metacognitive knowledge and field-based science learning in an outdoor environmental education program. In Zohar, A. & Dori, Y. (Eds.), Metacognition in science education: Trends in current research, contemporary trends and issues in science education (pp. 57-77). United States of America: Springer, Heidelberg.
Schraw, G, & Gutiérrez De Blume, A. (2015). Metacognitive strategy instruction that highlinghts the role of monitoring and control processes. In Peña-Ayala, A. (Ed.), Metacognition: Fundaments, applications and trends. A prolife of the current state -ofthe-art (pp. 3-15). New York: Springer.
Schraw, G. (2006). Knowledge: Structures and Processes. In Alexander, P. & Winne, P. (Eds.), Handbook of Educational Psychology (pp. 245-263). London: Routledge. https://doi.org/10.4324/9780203874790.ch11
Sawyer, K. (2014). The Cambridge handbook of the learning sciences. New York: Cambridge University Press.
Santa-Soriano, A., Lorenzo-Álvarez, C., & Torres-Valdés, R. (2018). Bibliometric analysis to identify an emerging research area: Public relations intelligence- a challenge to strengthen technological observatories in the network society. Scientometrics, 1591-1614. https://doi.org/https://doi.org/10.1007/s11192-018-2651-8
Rivers, M. L., Dunlosky, J., & Joynes, R. (2019). The contribution of classroom exams to formative evaluation of concept-level knowledge. Contemporary Educational Psychology, 59, 1-11. https://doi.org/10.1016/j.cedpsych.2019.101806
Hacker, D., Bol, L., & Keener, M. (2008). Metacognition in education: A focus on calibration. In Dunlosky, J.& Bjork, R. A. (Eds.), Handbook of metamemory and memory (pp. 429-455). New York: Psychology press.
Gutierrez, A. P., Schraw, G., Kuch, F., & Richmond, A. S. (2016). A two-process model of metacognitive monitoring : Evidence for general accuracy and error factors. Learning and Instruction, 44, 1-10. https://doi.org/10.1016/j.learninstruc.2016.02.006
Gutierrez, A. P., & Price, A. F. (2017). Calibration Between Undergraduate Students’ Prediction of and Actual Performance: The Role of Gender and Performance Attributions. Journal of Experimental Education, 85 (3), 486-500. https://doi.org/10.1080/00220973.2016.1180278
1
Ariel, R., & Karpicke, J. D. (2018). Improving Self-Regulated Learning With a Retrieval Practice Intervention. Journal of Experimental Psychology: Applied, 24 (1), 43-56. https://doi.org/10.1037/xap0000133
Agus, M., Peró-Cebollero, M., Guàrdia-Olmos, J., Portoghese, I., Mascia, M. L., & Penna, M. P. (2020). What’s about the calibration between confidence and accuracy? Findings in probabilistic problems from Italy and Spain. Eurasia Journal of Mathematics, Science and Technology Education, 16 (2). https://doi.org/10.29333/ejmste/113111
https://creativecommons.org/licenses/by-nc-sa/4.0/
Español
https://revistasojs.ucaldas.edu.co/index.php/latinoamericana/article/view/4273
Latinoamericana de Estudios Educativos
Universidad de Caldas
application/pdf
Artículo de revista
Núm. 1 , Año 2021 : Enero-Junio
17
Buratti, S., & Allwood, C. (2015). Regulating metacognitive processes-support for a metametacognitive ability. In Peña-Ayala, A. (Ed.), Metacognition: Fundaments, applications and trends. A prolife of the current state -of-the-art (pp. 17-35). New York: Springer.
autoeficacia
procesos cognitivos
aprendizaje
metamemoria
metacognición
Tamayo Alzate, Óscar Eugenio
Puente Ferreras, Aníbal
Orrego Cardozo, Mary
Montoya Londoño, Diana Marcela
Objetivo: establecer las tendencias conceptuales en la investigación sobre juicios metacognitivos en estudiantes universitarios. Método: se desarrolló una búsqueda en las bases de datos Web of Science y Scopus en el período 2016-2020 para artículos publicados en idioma inglés, atendiendo a la metodología de revisión sistemática. Una vez aplicados los criterios de depuración a la base de datos, se procedió a realizar los análisis descriptivos derivados. Resultados: se analizaron 21 artículos que cumplieron con los criterios de inclusión. Se encontraron 6 tendencias conceptuales entre las que se evidenció una importante orientación del campo hacia los estudios de monitoreo metacognitivo, además, de algunas nuevas tendencias que empiezan a emerger como los trabajos en medición de juicios, e igualmente el surgimiento de una tipología asociada con la evaluación formativa, que se ha denominado juicio evaluativo. Conclusión: en la parte final se presentan algunas implicaciones sobre el estado del desarrollo de la investigación.&amp;nbsp;
Avhustiuk, M. M., Pasichnyk, I. D., Kalamazh, R. V., Mykolaivna, M., Demydovych, I., & Volodymyrivna, R. (2018). The illusion of knowing in metacognitive monitoring: Effects of the type of information and of personal, cognitive, metacognitive, and individual psychological characteristics. Europe’s Journal of Psychology, 14 (2), 317-341. https://doi.org/10.5964/ejop.v14i2.1418
Publication
Callender, A. A., Franco-Watkins, A. M., & Roberts, A. S. (2016). Improving metacognition in the classroom through instruction, training, and feedback. Metacognition and Learning, 11 (2). https://doi.org/10.1007/s11409-015-9142-6
Dunlosky, J., & Metcalfe, J. (2009). Metacognition, A Texbook for cognitive, educational, life span, & applied psychology. United States of America: Sage publication, Inc.
González, M. J. P., Guzmán, M. F., & Chaviano, O. G. (2015). Criterios, clasificaciones y tendencias de los indicadores bibliométricos en la evaluación de la ciencia. Revista Cubana de Información en Ciencias de la Salud, 26 (3), 290-309. https://doi.org/10.1021/jp907259e
Glenberg, A., & Epstein, W. (1987). Calibration of comprehension. Memory & Cognition, 15 (1), 84-93. https://doi.org/10.3758/BF03197714
Frumos, F., & Grecu, S. (2019). Inaccuracy and overconfidence in metacognitive monitoring of university students. Revista de Cercerate Si Interventie Sociala, 66, 298-314.
Follmer, D. J., & Sperling, R. A. (2019). Examining the Role of Self-Regulated Learning Microanalysis in the Assessment of Learners’ Regulation. Journal of Experimental Education, 87 (2). https://doi.org/10.1080/00220973.2017.1409184
Fleming, S. M., & Lau, H. C. (2014). How to measure metacognition. Frontiers in Human Neuroscience, 8, 1-9. https://doi.org/10.3389/fnhum.2014.00443
Flavell, J. H. (Stanford U.) (1992). Perspectives on perspective taking. In H. Beilin & P. Pufall (Eds.), Piaget’s Theory: Prospects and possibilities. United States of America.: Erlbaum: Hillsdale.
Estany, A. (2013). La filosofía en el marco de las neurociencias. Revista de Neurología, 56 (6), 344-348.
Escalona-Fernández, M. I., Lagar-Barbosa, P., & Pulgarín, A. (2010). Web of Science vs. SCOPUS: un estudio cuantitativo en Ingeniería Química. Anales de Documentación, 13, 159-175. https://doi.org/10.6018/107121
Eflkides, A. (2008). Metacognition: Defining its facets and levels of functioning in relation to self- regulation and co-regulation. European Psychologist, 13 (4), 277-287. https://doi.org/10.1027/1016-9040.13.4.277
Dunlosky, J., & Thiede, K. W. (2013). Four cornerstones of calibration research: Why understanding students’ judgments can improve their achievement. Learning and Instruction, 24, 58-61. https://doi.org/https://doi.org/10.1016/j.learninstruc.2012.05.002
Dunlosky, J., & Tauber, S. K. (2012). Understanding people’s metacognitive judgments: an isomechanism framework and its implications for applied and theoretical research. In Perfect, T.& Lindsay, S. (Eds.), The SAGE Handbook of applied memory (pp. 1-10). London: Sage Publications inc.
Dunlosky, J., & Nelson, T. O. (1992). Importance of the kind of cue for judgments of learning (JOL) and the delayed-JOL effect, 20 (4), 374-380.
Camps, D. (2008). Limitaciones de los indicadores bibliométricos en la evaluación de la actividad científica biomédica. Colombia Medica, 39 (1), 74-79. Recuperado de https://bit.ly/3lvlDHD
Dunlosky, J., Bottiroli, S., & Hartwing, M. (2009). A call for representative desing in education science. In Handbook of Metacognition in Education (pp. 430-440). New York: Routledge.
De Granda- Orive, J., Alonso- Arroyo, A., & Roig-Vásquez, F. (2011). ¿Qué base de datos debemos emplear para nuestros análisis bibliográficos? Web of Science versus SCOPUS. Arch Bronconeumol, 47 (4), 213-217. https://doi.org/10.1186/1742-5581
Cogliano, M. C., Kardash, C. A. M., & Bernacki, M. L. (2019). The effects of retrieval practice and prior topic knowledge on test performance and confidence judgments. Contemporary Educational Psychology, 56. https://doi.org/10.1016/j.cedpsych.2018.12.001
Dunlosky, J., & Lipko, A. (2007). Metacomprehension: A brief history and how to improve its accuracy. Current Directions in Psychological Science, 16 (4), 228-232. https://doi.org/10.1111/j.1467-8721.2007.00509.x
Double, K. S., Birney, D. P., & Walker, S. A. (2018). A meta-analysis and systematic review of reactivity to judgements of learning. Memory, 26 (6), 741-750. https://doi.org/10.1080/09658211.2017.1404111
Dentakos, S., Saoud, W., Ackerman, R., & Toplak, M. E. (2019). Does domain matter? Monitoring accuracy across domains. Metacognition and Learning, 14 (3), 413-436. https://doi.org/10.1007/s11409-019-09198-4
De Granda-Orive, J. I. (2003). Algunas reflexiones y consideraciones sobre el factor de impacto. Archivos de Bronconeumología, 39 (9), 409-417. https://doi.org/10.1157/13050631
Cromley, J., & Azevedo, R. (2011). Measuring strategy use in context with multiple-choice items. Metacognition and Learning, 6 (2), 155-177. https://doi.org/10.1007/s11409-011-9070-z
De Bruin, A. B. H., Rikers, R. M. J. P., & Schmidt, H. G. (2005). Monitoring accuracy and self-regulation when learning to play a chess endgame. Applied Cognitive Psychology, 19 (2), 167-181. https://doi.org/10.1002/acp.1109
metacognition
Metacognitive judgments as an emerging research field. A systematic review (2016-2020)
cognitive processes
metamemory
learning
selfefficacy
Aim: To establish conceptual trends in research on metacognitive judgments in university students. Method: A search was carried out in the Web of Science and Scopus databases in the period from 2016 to 2020 for articles published in English, according to the systematic review methodology. Once the filtering criteria were applied to the database, the derived descriptive analyzes were carried out. Results: a total of 21 articles that met the inclusion criteria were analyzed. Six conceptual trends were found, among which an important orientation of the field towards metacognitive monitoring studies was evidenced, in addition to some new trends that are beginning to emerge such as the work on judgment measurement, and also the emergence of a typology associated with formative evaluation, which has been called evaluative judgment. Conclusion: The final part presents some implications on the state of the art of the development of the research.
Journal article
223
188
2020-01-01
2500-5324
https://revistasojs.ucaldas.edu.co/index.php/latinoamericana/article/download/4273/3930
10.17151/rlee.2021.17.1.10
2021-01-01T00:00:00Z
1900-9895
2021-01-01T00:00:00Z
https://doi.org/10.17151/rlee.2021.17.1.10
institution UNIVERSIDAD DE CALDAS
thumbnail https://nuevo.metarevistas.org/UNIVERSIDADDECALDAS/logo.png
country_str Colombia
collection Latinoamericana de Estudios Educativos
title Los juicios metacognitivos como un campo emergente de investigación. Una revisión sistemática (2016-2020)
spellingShingle Los juicios metacognitivos como un campo emergente de investigación. Una revisión sistemática (2016-2020)
Tamayo Alzate, Óscar Eugenio
Puente Ferreras, Aníbal
Orrego Cardozo, Mary
Montoya Londoño, Diana Marcela
autoeficacia
procesos cognitivos
aprendizaje
metamemoria
metacognición
metacognition
cognitive processes
metamemory
learning
selfefficacy
title_short Los juicios metacognitivos como un campo emergente de investigación. Una revisión sistemática (2016-2020)
title_full Los juicios metacognitivos como un campo emergente de investigación. Una revisión sistemática (2016-2020)
title_fullStr Los juicios metacognitivos como un campo emergente de investigación. Una revisión sistemática (2016-2020)
title_full_unstemmed Los juicios metacognitivos como un campo emergente de investigación. Una revisión sistemática (2016-2020)
title_sort los juicios metacognitivos como un campo emergente de investigación. una revisión sistemática (2016-2020)
title_eng Metacognitive judgments as an emerging research field. A systematic review (2016-2020)
description Objetivo: establecer las tendencias conceptuales en la investigación sobre juicios metacognitivos en estudiantes universitarios. Método: se desarrolló una búsqueda en las bases de datos Web of Science y Scopus en el período 2016-2020 para artículos publicados en idioma inglés, atendiendo a la metodología de revisión sistemática. Una vez aplicados los criterios de depuración a la base de datos, se procedió a realizar los análisis descriptivos derivados. Resultados: se analizaron 21 artículos que cumplieron con los criterios de inclusión. Se encontraron 6 tendencias conceptuales entre las que se evidenció una importante orientación del campo hacia los estudios de monitoreo metacognitivo, además, de algunas nuevas tendencias que empiezan a emerger como los trabajos en medición de juicios, e igualmente el surgimiento de una tipología asociada con la evaluación formativa, que se ha denominado juicio evaluativo. Conclusión: en la parte final se presentan algunas implicaciones sobre el estado del desarrollo de la investigación.&amp;nbsp;
description_eng Aim: To establish conceptual trends in research on metacognitive judgments in university students. Method: A search was carried out in the Web of Science and Scopus databases in the period from 2016 to 2020 for articles published in English, according to the systematic review methodology. Once the filtering criteria were applied to the database, the derived descriptive analyzes were carried out. Results: a total of 21 articles that met the inclusion criteria were analyzed. Six conceptual trends were found, among which an important orientation of the field towards metacognitive monitoring studies was evidenced, in addition to some new trends that are beginning to emerge such as the work on judgment measurement, and also the emergence of a typology associated with formative evaluation, which has been called evaluative judgment. Conclusion: The final part presents some implications on the state of the art of the development of the research.
author Tamayo Alzate, Óscar Eugenio
Puente Ferreras, Aníbal
Orrego Cardozo, Mary
Montoya Londoño, Diana Marcela
author_facet Tamayo Alzate, Óscar Eugenio
Puente Ferreras, Aníbal
Orrego Cardozo, Mary
Montoya Londoño, Diana Marcela
topicspa_str_mv autoeficacia
procesos cognitivos
aprendizaje
metamemoria
metacognición
topic autoeficacia
procesos cognitivos
aprendizaje
metamemoria
metacognición
metacognition
cognitive processes
metamemory
learning
selfefficacy
topic_facet autoeficacia
procesos cognitivos
aprendizaje
metamemoria
metacognición
metacognition
cognitive processes
metamemory
learning
selfefficacy
citationvolume 17
citationissue 1
citationedition Núm. 1 , Año 2021 : Enero-Junio
publisher Universidad de Caldas
ispartofjournal Latinoamericana de Estudios Educativos
source https://revistasojs.ucaldas.edu.co/index.php/latinoamericana/article/view/4273
language Español
format Article
rights http://purl.org/coar/access_right/c_abf2
info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/4.0/
references Metcalfe, J., & Kornell, N. (2005). A Region of Proximal Learning model of study time allocation. Journal of Memory and Language, 52 (4), 463-477. https://doi.org/10.1016/j.jml.2004.12.001
Pieger, E., Mengelkamp, C., & Bannert, M. (2017). Fostering Analytic Metacognitive Processes and Reducing Overconfidence by Disfluency: The Role of Contrast Effects. Applied Cognitive Psychology, 31 (3), 291-301. https://doi.org/10.1002/acp.3326
Petticrew, M., & Roberts, H. (2008). Systematic Reviews in the social sciences. New York: John Wiley y Sons, Ltd.
Paris, S., & Byrnes, J. (1989). The constructivist approach to self-regulation and learning in the classroom. In Zimmerman, B.& Schunk, D. (Eds.), Self -regulated learning and academic achievement (pp. 169-200). New York: Springer- Verlag.
Panadero, E., Broadbent, J., Boud, D., & Lodge, J. M. (2019). Using formative assessment to influence self- and co-regulated learning: the role of evaluative judgement. European Journal of Psychology of Education, 34 (3), 535-557. https://doi.org/10.1007/s10212-018-0407-8
Nelson, T. (1984). A comparison of current measures of the accuracy of feeling of knowing predictions. Psychological Bulletin, 95 (1), 109-133.
Nelson, T., & Narens, L. (1994). Why investigate metacognitive? In Metcalfe, J. & Shimamura, A. (Eds.), Metacognition: Knowing about knowing (pp. 1-25). United States of America.: The MIT Press Cambridge,.
Nelson, T. O., & Narens, L. (2000). Metamemory: A theoretical framework and new findings. The Psychology of Learning and Motivation, 26. https://doi.org/10.1016/S0079- 7421(08)60053-5
Nelson, T. O., & Leonesio, J. (1988). Allocation of Self-Paced Study Time and the “Laborin-Vain Effect”, 14 (4), 676-686.
Nelson, T. O. (1996). Gamma is a measure of the accuracy of predicting performance on one item relative to another item, not of the absolute performance on an individual item: Comments on schraw (1995). Applied Cognitive Psychology, 10 (3), 257-260. https://doi.org/10.1002/(SICI)1099-0720(199606)10:3<257::AID-ACP400>3.0.CO;2-9
Nelson, T. O. (1992). Metacognition: Core readings. Boston: Allyn and Bacon.
Moshman, D. (1979). To really get ahead, get a metatheory. In Kuhn, D. (Ed.), Intellectual development beyond childhood (pp. 59-68). United States of America: Jossey - Bass.
Morphew, J. W. (2020). Changes in metacognitive monitoring accuracy in an introductory physics course. Metacognition and Learning, 1-23. https://doi.org/10.1007/s11409-020-09239-3
Morphew, J. (2020). Changes in metacognitive monitoring accuracy in an introductory physics course. Metacognition and Learning. https://doi.org/10.1007/s11409-020-09239-3
McNamara, D. S. (2011). Measuring deep, reflective comprehension and learning strategies: Challenges and successes. Metacognition and Learning, 6 (2), 195-203. https://doi.org/10.1007/s11409-011-9082-8
Proust, J. (2010). Metacognition. Philosophy Compass, 11, 989-998.
McCutcheon, G. (1982). Facilitating teacher personal theorizing. In Ross, E., Cornett, & McCutcheon, G. (Eds.), Teacher personal theorizing: connecting curriculum practice, theory and research. New York: Albany, NY.
Mazancieux, A., Fleming, S., Souchay, C., & Moulin, C. (2020). Is there a G factor for metacognition? Correlations in retrospective metacognitive sensitivity across tasks. Journal of Experimental Psychology: General, 149 (9), 1788-1799. https://doi.org/10.1037/xge0000746
Kuhn, D. (1989). Children and adults as intuitive scientist. Psychol. Rev, 96, 674-689. Liberali, J. M., Reyna, V. F., Furlan, S., Stein, L. M., & Pardo, S. T. (2012). Individual Differences in Numeracy and Cognitive Reflection, with Implications for Biases and Fallacies in Probability Judgment. Journal of behavioral decision making, 25 (4, SI), 361-381. https://doi.org/10.1002/bdm.752
Kruger, J., & Dunning, D. (1999). Personality and Social Psychology Unskilled and Unaware of It : How Difficulties in Recognizing One’s Own Incompetence Lead to Inflated. Journal of Personality and Social Psychology, 77 (6), 1121-1134. https://doi.org/10.1037/0022-3514.77.6.1121
Koriat, A., Lichtenstein, S., & Fischhoff, B. (1980). Reasons for confidence. Journal of Experimental Psychology: Human Learning and Memory, 6 (2), 107-118.
Koriat, A. (1997). Monitoring One’s Own Knowledge During Study : A Cue-Utilization Approach to Judgments of Learning. Journal of Experimental Psychology: General, 126 (4), 349-370.
Kollmer, J., Schleinschok, K., Scheiter, K., & Eitel, A. (2020). Is drawing after learning effective for metacognitive monitoring only when supported by spatial scaffolds? Instructional Science, 48 (5), 569-589. https://doi.org/10.1007/s11251-020-09521-6
Higgins, J., & Green, S. (2008). Cochrane handbook for sytematic reviews of interventions. United States of America.: Wiley-Blackwell.
Hawker, M. J., Dysleski, L., & Rickey, D. (2016). Investigating General Chemistry Students Metacognitive Monitoring of Their Exam Performance by Measuring Postdiction Accuracies over Time. Journal of Chemical Education, 93 (5), 832-840. https://doi.org/10.1021/acs.jchemed.5b00705
Hart, J. (1965). Memory and the feeling-of-knowing experience. Journal of educational psychology, 56, 208-216.
Händel, M., Harder, B., & Dresel, M. (2020). Enhanced monitoring accuracy and test performance: Incremental effects of judgment training over and above repeated testing. Learning and Instruction, 65 (November 2018). https://doi.org/10.1016/j.learninstruc.2019.101245
Händel, M., & Fritzsche, E. S. (2016). Unskilled but subjectively aware: Metacognitive monitoring ability and respective awareness in low-performing students. Memory and Cognition, 44 (2), 1-13. https://doi.org/10.3758/s13421-015-0552-0
Händel, M., de Bruin, A. B. H., & Dresel, M. (2020). Individual differences in local and global metacognitive judgments. Metacognition and Learning, 15 (1), 51-75. https://doi.org/10.1007/s11409-020-09220-0
Hacker, D., Dunlosky, J., & Graesser, A. (2009). Handbook of Metacognition in Education. (D. Hacker, J. Dunlosky, & A. Graesser, Eds.). New York: Routledge journals, Taylor & Francis ltd. https://doi.org/10.4324/9780203876428
Pieger, E., Mengelkamp, C., & Bannert, M. (2016). Metacognitive judgments and dis fluency e Does disfluency lead to more accurate judgments, better control, and better performance? Learning and Instruction, 44, 31-40. https://doi.org/10.1016/j.learninstruc.2016.01.012
Quiles, C., Verdoux, H., & Prouteau, A. (2014). Assessing Metacognition during a Cognitive Task: Impact of “On-line” Metacognitive Questions on Neuropsychological Performances in a Non-clinical Sample (March 2015). https://doi.org/10.1017/S1355617714000290
Hacker, D., Bol, L., & Bahbahani, K. (2008). Explaining calibration accuracy in classroom contexts: the effects of incentives, reflection, and explanatory style. Metacognition and Learning, 2, 101-121.
Wagner-Menghin, M., de Bruin, A., van Merrienboer, J. J. G., & van Merriënboer, J. J. G. (2016). Monitoring communication with patients: analyzing judgments of satisfaction (JOS). Advances in Health Sciences Education, 21 (3), 523-540. https://doi.org/10.1007/s10459-015-9642-9
Zimmerman, B., & Moylan, A. (2009). Self -regulation: where metacognition and motivation intersect. In Hacker, D. J., Dunlosky, J. & Grasser, A. (Eds.), Handbook of Metacognition in Education (pp. 239-315). New York: Routledge.
Žauhar, V., Bajšanski, I., & Domijan, D. (2017). The influence of rule availability and item similarity on metacognitive monitoring during categorisation, 5911(November). https://doi.org/10.1080/20445911.2017.1396991
Winne, P., & Muis, K. (2011). Statistical estimates of learners’ judgments about knowledge in calibration of achievement. Metacognition and Learning, 6 (2), 179-193. https://doi.org/10.1007/s11409-011-9074-8
Winne, P., & Azevedo, R. (2014). Metacognition. In K. Sawyer (Ed.), The Cambridge Handbook of the Learning Sciences (pp. 63-87). New York: Cambridge University Press.
Wiley, J., Griffin, T. D., Jaeger, A. J., Jarosz, A. F., Cushen, P. J., & Thiede, K. W. (2016). Improving metacomprehension accuracy in an undergraduate course context. Journal of Experimental Psychology: Applied, 22 (4), 393-405. https://doi.org/10.1037/xap0000096
Wiley, J, Griffin, T., & Thiede, K. (2005). Putting the comprehension in metacomprehension. Journal of General Psychology, 132 (4), 408-428. https://doi.org/10.3200/ GENP.132.4.408-428
Temelman-Yogev, L., Katzir, T., & Prior, A. (2020). Monitoring comprehension in a foreign language: Trait or skill? Metacognition and Learning, 15 (3), 343-365. https://doi.org/10.1007/s11409-020-09245-5
Rhodes, M. G., & Tauber, S. K. (2011). The Influence of Delaying Judgments of Learning on Metacognitive Accuracy: A Meta-Analytic Review. Psychological Bulletin, 137 (1), 131-148. https://doi.org/10.1037/a0021705
Tai, J., Ajjawi, R., Boud, D., Dawson, P., & Panadero, E. (2018). Developing evaluative judgement: enabling students to make decisions about the quality of work. Higher Education, 76 (3), 467-481. https://doi.org/10.1007/s10734-017-0220-3
Segado-Boj, F. (2019). Búsqueda de información bibliográfica para la tesis doctoral Cómo y dónde buscar información para una tesis. Complutense de Madrid. Recuperado de https://eprints.ucm.es/58704/
Schraw, G., & Sperling-Dennison, R. (1994). Assesing metacognitive awareness. Contemporany Educational Psychology, 19, 460-475.
Schraw, G., Kuch, F., Gutierrez, A. P., & Richmond, A. S. (2014). Exploring a three-level model of calibration accuracy. Journal of Educational Psychology, 106 (4). https://doi.org/10.1037/a0036653
Schraw, G., Kuch, F., & Gutierrez, A. P. (2013). Measure for measure : Calibrating ten commonly used calibration scores. Learning and Instruction, 24, 48-57. https://doi.org/10.1016/j.learninstruc.2012.08.007
Schraw, G. (2009b). Measuring metacognitive judgments. In Hacker, D. J., Dunlosky, J. & Graesser, A. (Eds.), Handbook of Metacognition in Education (pp. 415-429). New York: Routledge.
Schraw, G. (2009a). A conceptual analysis of five measures of metacognitive monitoring. Metacognition and Learning, 4 (1), 33-45. https://doi.org/10.1007/s11409-008-9031-3
Schraw, G. (2002). Promoting general metacognitive awareness. In Hartman, H. (Ed.), Metacognition in learning and instruction: Theory, research and practice (pp. 3-16). London: Kluwer Academic.
Schraw, G, Olafson, L., Weibel, M., & Sewing, D. (2012). Metacognitive knowledge and field-based science learning in an outdoor environmental education program. In Zohar, A. & Dori, Y. (Eds.), Metacognition in science education: Trends in current research, contemporary trends and issues in science education (pp. 57-77). United States of America: Springer, Heidelberg.
Schraw, G, & Gutiérrez De Blume, A. (2015). Metacognitive strategy instruction that highlinghts the role of monitoring and control processes. In Peña-Ayala, A. (Ed.), Metacognition: Fundaments, applications and trends. A prolife of the current state -ofthe-art (pp. 3-15). New York: Springer.
Schraw, G. (2006). Knowledge: Structures and Processes. In Alexander, P. & Winne, P. (Eds.), Handbook of Educational Psychology (pp. 245-263). London: Routledge. https://doi.org/10.4324/9780203874790.ch11
Sawyer, K. (2014). The Cambridge handbook of the learning sciences. New York: Cambridge University Press.
Santa-Soriano, A., Lorenzo-Álvarez, C., & Torres-Valdés, R. (2018). Bibliometric analysis to identify an emerging research area: Public relations intelligence- a challenge to strengthen technological observatories in the network society. Scientometrics, 1591-1614. https://doi.org/https://doi.org/10.1007/s11192-018-2651-8
Rivers, M. L., Dunlosky, J., & Joynes, R. (2019). The contribution of classroom exams to formative evaluation of concept-level knowledge. Contemporary Educational Psychology, 59, 1-11. https://doi.org/10.1016/j.cedpsych.2019.101806
Hacker, D., Bol, L., & Keener, M. (2008). Metacognition in education: A focus on calibration. In Dunlosky, J.& Bjork, R. A. (Eds.), Handbook of metamemory and memory (pp. 429-455). New York: Psychology press.
Gutierrez, A. P., Schraw, G., Kuch, F., & Richmond, A. S. (2016). A two-process model of metacognitive monitoring : Evidence for general accuracy and error factors. Learning and Instruction, 44, 1-10. https://doi.org/10.1016/j.learninstruc.2016.02.006
Gutierrez, A. P., & Price, A. F. (2017). Calibration Between Undergraduate Students’ Prediction of and Actual Performance: The Role of Gender and Performance Attributions. Journal of Experimental Education, 85 (3), 486-500. https://doi.org/10.1080/00220973.2016.1180278
Ariel, R., & Karpicke, J. D. (2018). Improving Self-Regulated Learning With a Retrieval Practice Intervention. Journal of Experimental Psychology: Applied, 24 (1), 43-56. https://doi.org/10.1037/xap0000133
Agus, M., Peró-Cebollero, M., Guàrdia-Olmos, J., Portoghese, I., Mascia, M. L., & Penna, M. P. (2020). What’s about the calibration between confidence and accuracy? Findings in probabilistic problems from Italy and Spain. Eurasia Journal of Mathematics, Science and Technology Education, 16 (2). https://doi.org/10.29333/ejmste/113111
Buratti, S., & Allwood, C. (2015). Regulating metacognitive processes-support for a metametacognitive ability. In Peña-Ayala, A. (Ed.), Metacognition: Fundaments, applications and trends. A prolife of the current state -of-the-art (pp. 17-35). New York: Springer.
Avhustiuk, M. M., Pasichnyk, I. D., Kalamazh, R. V., Mykolaivna, M., Demydovych, I., & Volodymyrivna, R. (2018). The illusion of knowing in metacognitive monitoring: Effects of the type of information and of personal, cognitive, metacognitive, and individual psychological characteristics. Europe’s Journal of Psychology, 14 (2), 317-341. https://doi.org/10.5964/ejop.v14i2.1418
Callender, A. A., Franco-Watkins, A. M., & Roberts, A. S. (2016). Improving metacognition in the classroom through instruction, training, and feedback. Metacognition and Learning, 11 (2). https://doi.org/10.1007/s11409-015-9142-6
Dunlosky, J., & Metcalfe, J. (2009). Metacognition, A Texbook for cognitive, educational, life span, & applied psychology. United States of America: Sage publication, Inc.
González, M. J. P., Guzmán, M. F., & Chaviano, O. G. (2015). Criterios, clasificaciones y tendencias de los indicadores bibliométricos en la evaluación de la ciencia. Revista Cubana de Información en Ciencias de la Salud, 26 (3), 290-309. https://doi.org/10.1021/jp907259e
Glenberg, A., & Epstein, W. (1987). Calibration of comprehension. Memory & Cognition, 15 (1), 84-93. https://doi.org/10.3758/BF03197714
Frumos, F., & Grecu, S. (2019). Inaccuracy and overconfidence in metacognitive monitoring of university students. Revista de Cercerate Si Interventie Sociala, 66, 298-314.
Follmer, D. J., & Sperling, R. A. (2019). Examining the Role of Self-Regulated Learning Microanalysis in the Assessment of Learners’ Regulation. Journal of Experimental Education, 87 (2). https://doi.org/10.1080/00220973.2017.1409184
Fleming, S. M., & Lau, H. C. (2014). How to measure metacognition. Frontiers in Human Neuroscience, 8, 1-9. https://doi.org/10.3389/fnhum.2014.00443
Flavell, J. H. (Stanford U.) (1992). Perspectives on perspective taking. In H. Beilin & P. Pufall (Eds.), Piaget’s Theory: Prospects and possibilities. United States of America.: Erlbaum: Hillsdale.
Estany, A. (2013). La filosofía en el marco de las neurociencias. Revista de Neurología, 56 (6), 344-348.
Escalona-Fernández, M. I., Lagar-Barbosa, P., & Pulgarín, A. (2010). Web of Science vs. SCOPUS: un estudio cuantitativo en Ingeniería Química. Anales de Documentación, 13, 159-175. https://doi.org/10.6018/107121
Eflkides, A. (2008). Metacognition: Defining its facets and levels of functioning in relation to self- regulation and co-regulation. European Psychologist, 13 (4), 277-287. https://doi.org/10.1027/1016-9040.13.4.277
Dunlosky, J., & Thiede, K. W. (2013). Four cornerstones of calibration research: Why understanding students’ judgments can improve their achievement. Learning and Instruction, 24, 58-61. https://doi.org/https://doi.org/10.1016/j.learninstruc.2012.05.002
Dunlosky, J., & Tauber, S. K. (2012). Understanding people’s metacognitive judgments: an isomechanism framework and its implications for applied and theoretical research. In Perfect, T.& Lindsay, S. (Eds.), The SAGE Handbook of applied memory (pp. 1-10). London: Sage Publications inc.
Dunlosky, J., & Nelson, T. O. (1992). Importance of the kind of cue for judgments of learning (JOL) and the delayed-JOL effect, 20 (4), 374-380.
Camps, D. (2008). Limitaciones de los indicadores bibliométricos en la evaluación de la actividad científica biomédica. Colombia Medica, 39 (1), 74-79. Recuperado de https://bit.ly/3lvlDHD
Dunlosky, J., Bottiroli, S., & Hartwing, M. (2009). A call for representative desing in education science. In Handbook of Metacognition in Education (pp. 430-440). New York: Routledge.
De Granda- Orive, J., Alonso- Arroyo, A., & Roig-Vásquez, F. (2011). ¿Qué base de datos debemos emplear para nuestros análisis bibliográficos? Web of Science versus SCOPUS. Arch Bronconeumol, 47 (4), 213-217. https://doi.org/10.1186/1742-5581
Cogliano, M. C., Kardash, C. A. M., & Bernacki, M. L. (2019). The effects of retrieval practice and prior topic knowledge on test performance and confidence judgments. Contemporary Educational Psychology, 56. https://doi.org/10.1016/j.cedpsych.2018.12.001
Dunlosky, J., & Lipko, A. (2007). Metacomprehension: A brief history and how to improve its accuracy. Current Directions in Psychological Science, 16 (4), 228-232. https://doi.org/10.1111/j.1467-8721.2007.00509.x
Double, K. S., Birney, D. P., & Walker, S. A. (2018). A meta-analysis and systematic review of reactivity to judgements of learning. Memory, 26 (6), 741-750. https://doi.org/10.1080/09658211.2017.1404111
Dentakos, S., Saoud, W., Ackerman, R., & Toplak, M. E. (2019). Does domain matter? Monitoring accuracy across domains. Metacognition and Learning, 14 (3), 413-436. https://doi.org/10.1007/s11409-019-09198-4
De Granda-Orive, J. I. (2003). Algunas reflexiones y consideraciones sobre el factor de impacto. Archivos de Bronconeumología, 39 (9), 409-417. https://doi.org/10.1157/13050631
Cromley, J., & Azevedo, R. (2011). Measuring strategy use in context with multiple-choice items. Metacognition and Learning, 6 (2), 155-177. https://doi.org/10.1007/s11409-011-9070-z
De Bruin, A. B. H., Rikers, R. M. J. P., & Schmidt, H. G. (2005). Monitoring accuracy and self-regulation when learning to play a chess endgame. Applied Cognitive Psychology, 19 (2), 167-181. https://doi.org/10.1002/acp.1109
type_driver info:eu-repo/semantics/article
type_coar http://purl.org/coar/resource_type/c_6501
type_version info:eu-repo/semantics/publishedVersion
type_coarversion http://purl.org/coar/version/c_970fb48d4fbd8a85
type_content Text
publishDate 2020-01-01
date_accessioned 2021-01-01T00:00:00Z
date_available 2021-01-01T00:00:00Z
url https://revistasojs.ucaldas.edu.co/index.php/latinoamericana/article/view/4273
url_doi https://doi.org/10.17151/rlee.2021.17.1.10
issn 1900-9895
eissn 2500-5324
doi 10.17151/rlee.2021.17.1.10
citationstartpage 188
citationendpage 223
url2_str_mv https://revistasojs.ucaldas.edu.co/index.php/latinoamericana/article/download/4273/3930
_version_ 1823196324229545984

Código QR

Estadísticas y Métricas Alternativas

Títulos similares