Revisión de Tecnologías Educativas que Fomentan la Lectura de Comprensión Autónoma
DOI:
https://doi.org/10.5753/rbie.2021.29.0.980Abstract
La lectura es una actividad importante tanto en la vida diaria como en la académica. A pesar de que los planes curriculares marcan objetivos bien definidos para cada grado de estudios, la lectura no se aplica extensivamente en el aula por ser altamente demandante en carga cognitiva y tiempo. Fuera del aula, los estudiantes carecen de la guía del docente, si bien pueden hacer uso de otros recursos y estrategias como hacer anotaciones, elaborar diagramas, redactar resúmenes, entre otras, para comprender los textos. El apoyo a la comprensión lectora es un desafío en el ámbito tecnológico, la tarea se encuentra dentro de los dominios llamados mal definidos, donde no existe una única respuesta correcta. En este trabajo se presenta una revisión parcial con el objetivo de identificar tecnología educativa propuesta en los últimos años que contribuye directa o indirectamente a la comprensión lectora autónoma. Se hace una breve comparación indicando objetivos y características. Finalmente, se señalan los retos futuros.
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Allen, L. K., Likens, A., Perret, C., & McNamara, D. S. (2017). What’d you say again? Recurrence quantification analysis as a method for analyzing the dynamics of discourse in a reading strategy tutor. Proceedings of the Seventh International Learning Analytics & Knowledge Conference, 373–382. doi: 10.1145/3027385.3027445 [GS Search]
Allen, L. K., Perret, C., Mills, C., & McNamara, D. S. (2019). Are you talking to me? Multi-dimensional language analysis of explanations during reading. Proceedings of the 9th International Conference on Learning Analytics & Knowledge (LAK19), 116–120. doi: 10.1145/3303772.3303835 [GS Search]
Allen, L. K., Snow, E. L., & McNamara, D. S. (2015). Are you reading my mind? Modeling students’ reading comprehension skills with natural language processing techniques. ACM International Conference Proceeding Series, 16-20-Marc, 246–254. doi: 10.1145/2723576.2723617 [GS Search]
Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, R. (1995). Cognitive Tutors: Lessons Learned. Journal of the Learning Sciences, 4(2), 167–207. doi: 10.1207/s15327809jls0402_2 [GS Search]
Baer, W. O., Cheng, Q., McGlown, C., Gong, Y., Cai, Z., & Graesser, A. C. (2016). Using Virtual Agents to Deliver Lessons in Reading Comprehension to Struggling Adult Learners. In D. Traum, W. Swartout, P. Khooshabeh, S. Kopp, S. Scherer, & A. Leuski (Eds.), International Conference on Intelligent Virtual Agents (Vol. 10011, pp. 516–518). Springer International Publishing. doi: 10.1007/978-3-319-47665-0_67 [GS Search]
Cataldi, Z., & Lage, F. J. (2009). Sistemas tutores inteligentes orientados a la enseñanza para la comprensión. Revista Electrónica de Tecnología Educativa, 1–19. doi: 10.21556/edutec.2009.28.456 [GS Search]
Chaudhri, V. K., Overholtzer, A., & Spaulding, A. (2015). An Intelligent Textbook that Answers Questions. In P. Lambrix, E. Hyvönen, E. Blomqvist, V. Presutti, G. Qi, U. Sattler, Y. Ding, & C. Ghidini (Eds.), International Conference on Knowledge Engineering and Knowledge Management (Vol. 8982, Issue 2, pp. 131–135). Springer International Publishing. doi: 10.1007/978-3-319-17966-7_16 [GS Search]
Chiang, K., Fan, C., Liu, H., & Chen, G. (2016). Effects of a computer-assisted argument map learning strategy on sixth-grade students’ argumentative essay reading comprehension. Multimedia Tools and Applications, 75(16), 9973–9990. doi: 10.1007/s11042-015-2904-y [GS Search]
Crossley, S., Allen, L. K., Snow, E. L., & McNamara, D. S. (2015). Pssst... textual features... there is more to automatic essay scoring than just you! Proceedings of the Fifth International Conference on Learning Analytics And Knowledge - LAK ’15, 203–207. doi: 10.1145/2723576.2723595 [GS Search]
Fadel, C., Lead, G., & Systems, C. (2008). 21st Century Skills: How can you prepare students for the new Global Economy, Cisco Systems and OECD, Paris. https://www.oecd.org/site/educeri21st/40756908.pdf [GS Search]
Fang, Y., Lippert, A., Cai, Z., Hu, X., & Graesser, A. C. (2019). A Conversation-Based Intelligent Tutoring System Benefits Adult Readers with Low Literacy Skills. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Vol. 11597 LNCS (pp. 604–614). Springer International Publishing. doi: 10.1007/978-3-030-22341-0_47 [GS Search]
Feng, S., Stewart, J., Clewley, D., & Graesser, A. C. (2015). Emotional, Epistemic, and Neutral Feedback in AutoTutor Trialogues to Improve Reading Comprehension. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9112, pp. 570–573). doi: 10.1007/978-3-319-19773-9_64 [GS Search]
Hock, M., & Mellard, D. (2005). Reading Comprehension Strategies for Adult Literacy Outcomes. Journal of Adolescent & Adult Literacy, 49(3), 192–200. doi: 10.1598/JAAL.49.3.3 [GS Search]
Icaza-Álvarez, D. O., Campoverde-Jiménez, G. E., Verdugo-Ormaza, D. E., & Arias-Reyes, P. D. (2019). El analfabetismo tecnológico o digital. Polo Del Conocimiento, 4(2), 393. doi: 10.23857/pc.v4i2.922 [GS Search]
INEGI. (2020, 14 de mayo). Estadística a propósito del día mundial del internet (17 de mayo) datos nacionales. [Comunicado de Prensa Núm. 216/20].
Jacovina, M. E., & McNamara, D. S. (2016). Intelligent tutoring systems for literacy: Existing technologies and continuing challenges. In Intelligent Tutoring Systems: Structure, Applications and Challenges (pp. 153–174). Nova Science Publishers Inc. [GS Search]
Jacovina, M. E., Tanner Jackson, G., Snow, E. L., & McNamara, D. S. (2016). Timing Game-Based Practice in a Reading Comprehension Strategy Tutor. In A. Micarelli, J. Stamper, & K. Panourgia (Eds.), Intelligent Tutoring Systems (Vol. 9684, pp. 59–68). Springer International Publishing. doi: 10.1007/978-3-319-39583-8_6 [GS Search]
Johnson, A. M., Guerrero, T. A., Tighe, E. L., & McNamara, D. S. (2017). iSTART-ALL: Confronting Adult Low Literacy with Intelligent Tutoring for Reading Comprehension. In Aied 2017 (Vol. 1, Issue August 2018, pp. 125–136). doi: 10.1007/978-3-319-61425-0_11 [GS Search]
Li, H., & Graesser, A. (2017). Impact of Pedagogical Agents’ Conversational Formality on Learning and Engagement. In E. André, R. Baker, X. Hu, M. M. T. Rodrigo, and B. du Boulay (Eds.), International Conference on Artificial Intelligence in Education (Vol. 10331, pp. 188–200). Springer International Publishing. doi: 10.1007/978-3-319-61425-0_16 [GS Search]
McCarthy, K. S., Jacovina, M. E., Snow, E. L., Guerrero, T. A., & McNamara, D. S. (2017). iSTART Therefore I Understand: But Metacognitive Supports Did not Enhance Comprehension Gains. International Conference on Artificial Intelligence in Education, 1, 201–211. doi: 10.1007/978-3-319-61425-0_17 [GS Search]
McCarthy, K. S., Likens, A. D., Johnson, A. M., Guerrero, T. A., & McNamara, D. S. (2018). Metacognitive Overload!: Positive and Negative Effects of Metacognitive Prompts in an Intelligent Tutoring System. International Journal of Artificial Intelligence in Education, 28(3), 420–438. doi: 10.1007/s40593-018-0164-5 [GS Search]
McCarthy, K. S., Soto, C., Malbrán, C., Fonseca, L., Simian, M., & McNamara, D. S. (2018). iSTART-E: Reading Comprehension Strategy Training for Spanish Speakers. In International Conference on Artificial Intelligence in Education, 1(August), 215–219. doi: 10.1007/978-3-319-93846-2_39 [GS Search]
McCarthy, K. S., Watanabe, M., Dai, J., & McNamara, D. S. (2020). Personalized learning in iSTART: Past modifications and future design. Journal of Research on Technology in Education, 52(3), 301–321. doi: 10.1080/15391523.2020.1716201 [GS Search]
Meyer, B. J. ., Brandt, D. M., & Bluth, G. J. (1980). Use of Top-Level Structure in Text: Key for Reading Comprehension of Ninth-Grade Students. Reading Research Quarterly, 16(1), 72–103. doi: 10.2307/747349 [GS Search]
Michelucci (Ed.). (2013). Handbook of Human Computation. Springer New York. doi: 10.1007/978-1-4614-8806-4 [GS Search]
Morfidi, E., Mikropoulos, A., & Rogdaki, A. (2018). Using concept mapping to improve poor readers’ understanding of expository text. Education and Information Technologies, 23(1), 271–286. doi: 10.1007/s10639-017-9600-7 [GS Search]
Novak, J. D., & Cañas, A. J. (2008). The Theory Underlying Concept Maps and How to Construct and Use Them. [GS Search]
Okoli, C., & Schabram, K. (2012). A Guide to Conducting a Systematic Literature Review of Information Systems Research. SSRN Electronic Journal, 10(2010). doi: 10.2139/ssrn.1954824 [GS Search]
Olney, A. M., & Cade, W. L. (2015). Authoring Intelligent Tutoring Systems Using Human Computation: Designing for Intrinsic Motivation. In D. D. Schmorrow & C. M. and Fidopiastis (Eds.), Foundations of Augmented Cognition (pp. 628–639). Springer International Publishing. doi: 10.1007/978-3-319-20816-9_60 [GS Search]
Omheni, N., & Kacem, A. H. (2016). “i-Read”: A Collaborative Learning Environment to Support Students with Low Reading Abilities. International Conference on Intelligent Tutoring Systems, 9684, 221–226. doi: 10.1007/978-3-319-39583-8_21 [GS Search]
Perret, C. A., Johnson, A. M., McCarthy, K. S., Guerrero, T. A., Dai, J., & McNamara, D. S. (2017). StairStepper: An Adaptive Remedial iSTART Module. International Conference on Artificial Intelligence in Education, 557–560. doi: 10.1007/978-3-319-61425-0_63 [GS Search]
Ricci, F., Rokach, L., & Shapira, B. (Eds.). (2015). Recommender Systems Handbook. Springer US. doi: 10.1007/978-1-4899-7637-6 [GS Search]
Shen, W., Lin, J.-M., & Hong, Z.-W. (2018). An Extensive Reading System Built on the Basis of Comprehensible Input Principles - A Key to Rescuing the Lower-Level EFL University Students’ Vocabulary Ability. International Conference on Innovative Technologies and Learning, i, 536–545. doi: 10.1007/978-3-319-99737-7_57 [GS Search]
Shi, G., Lippert, A. M., Shubeck, K., Fang, Y., Chen, S., Pavlik, P., Greenberg, D., & Graesser, A. C. (2018). Exploring an intelligent tutoring system as a conversation-based assessment tool for reading comprehension. Behaviormetrika, 45(2), 615–633. doi: 10.1007/s41237-018-0065-9 [GS Search]
Snow, E. L., Allen, L. K., Jackson, G. T., & McNamara, D. S. (2015). Spendency: Students’ Propensity to Use System Currency. International Journal of Artificial Intelligence in Education, 25(3), 407–427. doi: 10.1007/s40593-015-0044-1 [GS Search]
Snow, E. L., McNamara, D. S., Jacovina, M. E., Allen, L. K., Johnson, A. M., Perret, C. A., Dai, J., Tanner Jackson, G., Likens, A. D., Russell, D. G., & Weston, J. L. (2015). Promoting Metacognitive Awareness within a Game-Based Intelligent Tutoring System. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9112, pp. 786–789). doi: 10.1007/978-3-319-19773-9_116 [GS Search]
Walker, E., Wong, A., Fialko, S., Restrepo, M. A., & Glenberg, A. M. (2017). EMBRACE: Applying Cognitive Tutor Principles to Reading Comprehension. In International Conference on Artificial Intelligence in Education 2017 (Vol. 1, pp. 578–581). doi: 10.1007/978-3-319-61425-0_68 [GS Search]
Wijekumar, K. K., Meyer, B. J. F., Lei, P., Cheng, W., Ji, X., & Joshi, R. M. (2017). Evidence of an Intelligent Tutoring System as a Mindtool to Promote Strategic Memory of Expository Texts and Comprehension With Children in Grades 4 and 5. Journal of Educational Computing Research, 55(7), 1022–1048. doi: 10.1177/0735633117696909 [GS Search]
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