Abstract
This study compared the effects of extracurricular synchronous computer-mediated communication (SCMC) and asynchronous computer-mediated communication (ASCMC) between students and teachers on students’ digital reading performance at different frequencies. 392,269 samples from 53 countries/regions that participated in the Programme for International Student Assessment 2018 were collected. Multilevel regression analysis showed that SCMC negatively influenced digital reading performance across countries/regions. As the frequency decreased, the negative effect of SCMC diminished. In contrast, ASCMC at a moderately low frequency could facilitate digital reading performance in some countries/regions; however, as frequency increased, the positive effect became negative. These results showed that synchronicity played a role in predicting students’ digital reading performance. This study also explored the mediating effect of metacognition with Nelson and Naren’s metacognitive control-monitoring model. A multilevel mediation analysis proved that the effects of SCMC and ASCMC on digital reading performance were mediated by students’ metacognition of assessing credibility. Practical implications and suggestions for students’ self-paced learning were discussed with the purpose of promoting the effective use of extracurricular CMC between students and teachers and improving students’ digital reading achievement in the post-COVID-19 pandemic era.
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The dataset that this study based on are available in the official website of PISA (URL: http://www.oecd.org/pisa/data/2018database/). All data provided or analyzed in this study are included in this published article (and its supplemental files).
References
Abendroth, J., & Richter, T. (2021). How to understand what you don’t believe: Metacognitive training prevents belief-biases in multiple text comprehension. Learning and Instruction, 71, 101394. https://doi.org/10.1016/j.learninstruc.2020.101394.
Abrams, Z. I. (2003). The effect of synchronous and asynchronous CMC on oral performance in German. Modern Language Journal, 87(2), 157–167. https://doi.org/10.1111/1540-4781.00184.
AbuSeileek, A. F., & Qatawneh, K. (2013). Effects of synchronous and asynchronous computer-mediated communication (CMC) oral conversations on English language learners’ discourse functions. Computers & Education, 62, 181–190. https://doi.org/10.1016/j.compedu.2012.10.013.
Adam, T., & Tatnall, A. (2017). The value of using ICT in the education of school students with learning difficulties. Education and Information Technologies, 22(6), 2711–2726. https://doi.org/10.1007/s10639-017-9605-2.
Angeli, C., & Schwartz, N. H. (2016). Differences in electronic exchanges in synchronous and asynchronous computer-mediated communication: The effect of culture as a mediating variable. Interactive Learning Environments, 24(6), 1109–1130. https://doi.org/10.1080/10494820.2014.961484.
Arpaci, S., Mercan, F. C., & Arikan, S. (2021). The differential relationships between PISA 2015 science performance and, ICT availability, ICT use and attitudes toward ICT across regions: Evidence from 35 countries. Education and Information Technologies, 26(5), 6299–6318. https://doi.org/10.1007/s10639-021-10576-2.
Artelt, C., & Schneider, W. (2015). Cross-country generalizability of the role of metacognitive knowledge in students’ strategy use and reading competence. Teachers College Record, 117(1), Article 010304. Retrieved April 13, 2022, from https://www.tcrecord.org/Content.asp?ContentId=17695
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173.
Chang, W. H., Huang, T. H., & Liu, Y. C. (2019). Influence of an interactive e-book on the reading comprehension of different ethnic groups using Indigenous culture as content. International Journal of Human–Computer Interaction, 35(4–5), 323–332. https://doi.org/10.1080/10447318.2018.1543079.
Chen, J., Zhang, Y., & Hu, J. (2021a). Synergistic effects of instruction and affect factors on high- and low-ability disparities in elementary students’ reading literacy. Reading and Writing: An Interdisciplinary Journal, 34(1), 199–230. https://doi.org/10.1007/s11145-020-10070-0
Chen, J., Zhang, Y., Wei, Y., & Hu, J. (2021b). Discrimination of the contextual features of top performers in scientific literacy using a machine learning approach. Research in Science Education, 51(Suppl. 1), 129–158. https://doi.org/10.1007/s11165-019-9835-y
Chen, X., & Hu, J. (2020). ICT-related behavioral factors mediate the relationship between adolescents’ ICT interest and their ICT self-efficacy: Evidence from 30 countries. Computers & Education, 159, Article 104004. https://doi.org/10.1016/j.compedu.2020.104004
Christopher, M. M., Thomas, J. A., & Tallent-Runnels, M. K. (2004). Raising the bar: Encouraging high level thinking in online discussion forums. Roeper Review, 26(3), 166–171. https://doi.org/10.1080/02783190409554262.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Erlbaum.
Coiro, J., & Dobler, E. (2007). Exploring the online reading comprehension strategies used by sixth-grade skilled readers to search for and locate information on the Internet. Reading Research Quarterly, 42(2), 214–257. https://doi.org/10.1598/RRQ.42.2.2.
Cunningham, D. J. (2016). Request modification in synchronous computer-mediated communication: The role of focused instruction. Modern Language Journal, 100(2), 484–507. https://doi.org/10.1111/modl.12332.
Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22. https://doi.org/10.1177/0047239520934018.
Dignath, C., Buettner, G., & Langfeldt, H. P. (2008). How can primary school students learn self-regulated learning strategies most effectively? A meta-analysis on self-regulation training programmes. Educational Research Review, 3(2), 101–129. https://doi.org/10.1016/j.edurev.2008.02.003.
Eickelmann, B., Gerick, J., & Koop, C. (2017). ICT use in mathematics lessons and the mathematics achievement of secondary school students by international comparison: Which role do school level factors play? Education and Information Technologies, 22(4), 1527–1551. https://doi.org/10.1007/s10639-016-9498-5.
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American Psychologist, 34(10), 906–911. https://doi.org/10.1037/0003-066X.34.10.906.
Giesbers, B., Rienties, B., Tempelaar, D., & Gijselaers, W. (2014). A dynamic analysis of the interplay between asynchronous and synchronous communication in online learning: The impact of motivation. Journal of Computer Assisted Learning, 30(1), 30–50. https://doi.org/10.1111/jcal.12020.
Hahnel, C., Goldhammer, F., Kroehne, U., & Naumann, J. (2018). The role of reading skills in the evaluation of online information gathered from search engine environments. Computers in Human Behavior, 78, 223–234. https://doi.org/10.1016/j.chb.2017.10.004.
Hardy, M. A. (1993). Regression with dummy variables. Sage.
Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76(4), 408–420. https://doi.org/10.1080/03637750903310360.
Hayes, A. F. (2013). Introduction to mediation, moderation and conditional process analysis: A regression-based approach. Guilford Press.
Hayes, A. F., & Preacher, K. J. (2014). Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical & Statistical Psychology, 67(3), 451–470. https://doi.org/10.1111/bmsp.12028.
Herborn, K., Stadler, M., Mustafic, M., & Greiff, S. (2020). The assessment of collaborative problem solving in PISA 2015: Can computer agents replace humans? Computers in Human Behavior, 104, 105624. https://doi.org/10.1016/j.chb.2018.07.035.
Hu, J. (2014). An analysis of the design process of a language learning management system. Control and Intelligent Systems, 42(1), 80–86. https://doi.org/10.2316/Journal.201.2014.1.201-2534.
Hu, J., Dong, X., & Peng, Y. (2022). Discovery of the key contextual factors relevant to the reading performance of elementary school students from 61 countries/regions: Insight from a machine learning-based approach. Reading and Writing: An Interdisciplinary Journal, 35(1), 93–127. https://doi.org/10.1007/s11145-021-10176-z.
Hu, J., & Yu, R. (2021). The effects of ICT-based social media on adolescents’ digital reading performance: A longitudinal study of PISA 2009, PISA 2012, PISA 2015 and PISA 2018. Computers & Education, 175, 104342. https://doi.org/10.1016/j.compedu.2021.104342.
Jonassen, D., Davidson, M., Collins, M., Campbell, J., & Haag, B. B. (1995). Constructivism and computer-mediated communication in distance education. American Journal of Distance Education, 9(2), 7–26. https://doi.org/10.1080/08923649509526885.
Junco, R., Heiberger, G., & Loken, E. (2011). The effect of Twitter on college student engagement and grades. Journal of Computer Assisted Learning, 27(2), 119–132. https://doi.org/10.1111/j.1365-2729.2010.00387.x.
Kirschner, P. A., & Karpinski, A. C. (2010). Facebook (R) and academic performance. Computers in Human Behavior, 26(6), 1237–1245. https://doi.org/10.1016/j.chb.2010.03.024.
Kramer, O. (2013). K-Nearest Neighbors. dimensionality reduction with unsupervised nearest neighbors (pp. 13–23). Springer Berlin Heidelberg.
Lang, F., Kammerer, Y., Stürmer, K., & Gerjets, P. (2021). Investigating professed and enacted epistemic beliefs about the uncertainty of scientific knowledge when students evaluate scientific controversies. European Journal of Psychology of Education, 36(1), 125–146. https://doi.org/10.1007/s10212-020-00471-8.
Lau, K. L., & Chan, D. W. (2003). Reading strategy use and motivation among Chinese good and poor readers in Hong Kong. Journal of Research in Reading, 26(2), 177–190. https://doi.org/10.1111/1467-9817.00195.
Law, A. S., & Stock, R. (2019). Learning approach and its relationship to type of media use and frequency of media-multitasking. Active Learning in Higher Education, 20(2), 127–138. https://doi.org/10.1177/1469787417735612.
Lee, Y. H., & Wu, J. Y. (2013). The indirect effects of online social entertainment and information seeking activities on reading literacy. Computers & Education, 67, 168–177. https://doi.org/10.1016/j.compedu.2013.03.001.
Lim, H. J., & Jung, H. (2019). Factors related to digital reading achievement: A multi-level analysis using international large scale data. Computers & Education, 133, 82–93. https://doi.org/10.1016/j.compedu.2019.01.007.
Maier, J., & Richter, T. (2013). How nonexperts understand conflicting information on social science issues: The role of perceived plausibility and reading goals. Journal of Media Psychology-Theories Methods and Applications, 25(1), 14–26. https://doi.org/10.1027/1864-1105/a000078.
Mason, L., Boldrin, A., & Ariasi, N. (2010). Searching the web to learn about a controversial topic: Are students epistemically active? Instructional Science, 38(6), 607–633. https://doi.org/10.1007/s11251-008-9089-y.
McNeil, L. (2014). Ecological affordance and anxiety in an oral asynchronous computer-mediated environment. Language Learning & Technology, 18(1), 142–159. Retrieved April 13, 2022, from http://llt.msu.edu/issues/february2014/mcneil.pdf
Melanlioglu, D. (2014). Impact of metacognitive strategies instruction on secondary school students’ reading anxieties. Egitim Ve Bilim-Education and Science, 39(176), 107–119. Retrieved from https://doi.org/10.15390/EB.2014.3540
Mijuskovic, M., & Simovic, S. (2016). The 21st century English language reading classroom in Montenegro: The influence of metacognitive strategies on university students’ attitudes regarding the process of reading in English. Porta Linguarum, 26, 23–36. Retrieved April 13, 2022, from http://www.ugr.es/~portalin/articulos/PL_numero26/ART2_Marija%20Mijuskovic.pdf
Miyamoto, A., Pfost, M., & Artelt, C. (2019). The relationship between intrinsic motivation and reading comprehension: Mediating effects of reading amount and metacognitive knowledge of strategy use. Scientific Studies of Reading, 23(6), 445–460. https://doi.org/10.1080/10888438.2019.1602836.
Mokhtari, K., & Reichard, C. A. (2002). Assessing students’ metacognitive awareness of reading strategies. Journal of Educational Psychology, 94(2), 249–259. https://doi.org/10.1037//0022-0663.94.2.249.
Nelson, T. O., & Narens, L. (1990). Metamemory: A theoretical framework and new findings. Psychology of Learning and Motivation, 26, 125–173. https://doi.org/10.1016/S0079-7421(08)60053-5.
Niemann, D., Martens, K., & Teltemann, J. (2017). PISA and its consequences: Shaping education policies through international comparisons. European Journal of Education, 52(2), 175–183. https://doi.org/10.1111/ejed.12220.
OECD (2017). PISA technical report. OECD Publishing.
OECD. (2019). PISA 2018 assessment and analytical framework. OECD Publishing.
Ogbonna, C. G., Ibezim, N. E., & Obi, C. A. (2019). Synchronous versus asynchronous e-learning in teaching word processing: An experimental approach. South African Journal of Education, 39(2). https://doi.org/10.15700/saje.v39n2a1383
Oztok, M., Zingaro, D., Brett, C., & Hewitt, J. (2013). Exploring asynchronous and synchronous tool use in online courses. Computers & Education, 60(1), 87–94. https://doi.org/10.1016/j.compedu.2012.08.007.
Paul, J. A., Baker, H. M., & Cochran, J. D. (2012). Effect of online social networking on student academic performance. Computers in Human Behavior, 28(6), 2117–2127. https://doi.org/10.1016/j.chb.2012.06.016.
Pérez, L. (2003). Foreign language productivity in synchronous versus asynchronous computer-mediated communication. CALICO Journal, 21(1), 89–104. https://doi.org/10.1558/cj.v21i1.89-104.
R Core Team. (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Available online at: https://www.R-project.org/. Accessed 26 Oct 2021.
Razagifard, P. (2013). The impact of text-based CMC on improving L2 oral fluency. Journal of Computer Assisted Learning, 29(3), 270–279. https://doi.org/10.1111/jcal.12000.
Riordan, M. A., & Kreuz, R. J. (2010). Emotion encoding and interpretation in computer-mediated communication: Reasons for use. Computers in Human Behavior, 26(6), 1667–1673. https://doi.org/10.1016/j.chb.2010.06.015.
Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statal Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02.
Schünemann, N., Spörer, N., & Brunstein, J. (2013). Integrating self-regulation in whole-class reciprocal teaching: A moderator–mediator analysis of incremental effects on fifth graders’ reading comprehension. Contemporary Educational Psychology, 38, 289–305. https://doi.org/10.1016/j.cedpsych.2013.06.002.
Shang, H. F. (2005). Email dialogue journaling: Attitudes and impact on L2 reading performance. Educational Studies, 31(2), 197–212. https://doi.org/10.1080/03055690500095597.
Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling (2nd ed.). Sage Publications.
Sobel, M. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, 290–312. https://doi.org/10.2307/270723.
Srijamdee, K., & Pholphirul, P. (2020). Does ICT familiarity always help promote educational outcomes? Empirical evidence from PISA-Thailand. Education and Information Technologies, 25(4), 2933–2970. https://doi.org/10.1007/s10639-019-10089-z.
Stadler, M., Herborn, K., Mustafic, M., & Greiff, S. (2020). The assessment of collaborative problem solving in PISA 2015: An investigation of the validity of the PISA 2015 CPS tasks. Computers & Education, 157, Article 103964. https://doi.org/10.1016/j.compedu.2020.103964
Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s Alpha. International Journal of Medical Education, 2, 53–55. https://doi.org/10.5116/ijme.4dfb.8dfd.
Thiede, K. W., Anderson, M. C. M., & Therriault, D. (2003). Accuracy of metacognitive monitoring affects learning of texts. Journal of Educational Psychology, 95(1), 66–73. https://doi.org/10.1037/0022-0663.95.1.66.
Torgo, L. (2017). Data mining with R: Learning with case studies (2nd ed.). Chapman and Hall/CRC Press.
Tyler, J. R., & Tang, J. C. (2003). When can I expect an email response? A study of rhythms in email usage. Proceedings of ECSCW 2003 (pp.239–258). Springer. Retrieved October 12, 2021, from https://www.hpl.hp.com/research/idl/papers/rhythms/ECSCWFinal.pdf
Veas, A., Castejon, J. L., Minano, P., & Gilar-Corbi, R. (2019). Relationship between parent involvement and academic achievement through metacognitive strategies: A multiple multilevel mediation analysis. British Journal of Educational Psychology, 89(2), 393–411. https://doi.org/10.1111/bjep.12245.
Wu, J. Y. (2014). Gender differences in online reading engagement, metacognitive strategies, navigation skills and reading literacy. Journal of Computer Assisted Learning, 30(3), 252–271. https://doi.org/10.1111/jcal.12054.
Wu, J. Y., & Peng, Y. C. (2017). The modality effect on reading literacy: Perspectives from students’ online reading habits, cognitive and metacognitive strategies, and web navigation skills across regions. Interactive Learning Environments, 25(7), 859–876. https://doi.org/10.1080/10494820.2016.1224251.
Xiao, Y., & Hu, J. (2019). The moderation examination of ICT use on the association between Chinese mainland students’ socioeconomic status and reading achievement. International Journal of Emerging Technologies in Learning, 14(15), 107–120. https://doi.org/10.3991/ijet.v14i15.10494.
Xiao, Y., Liu, Y., & Hu, J. (2019). Regression analysis of ICT impact factors on early adolescents’ reading proficiency in five high-performing countries. Frontiers in Psychology, 10, Article 1646. https://doi.org/10.3389/fpsyg.2019.01646
Yang, S. H. (2009). Using blogs to enhance critical reflection and community of practice. Educational Technology & Society, 12(2), 11–21. Retrieved October 12, 2021, from https://www.ds.unipi.gr/et&s/journals/12_2/2.pdf
Yang, X., Zhou, X., & Hu, J. (2022). Students’ preferences for seating arrangements and their engagement in cooperative learning activities in college English blended learning classrooms in higher education. Higher Education Research & Development, 41(4), 1356–1371. https://doi.org/10.1080/07294360.2021.1901667.
Yu, H., & Hu, J. (2022a). ICT self-efficacy and ICT interest mediate the gender differences in digital reading: A multilevel serial mediation analysis. International Journal of Emerging Technologies in Learning, 17(05), 211–225. https://doi.org/10.3991/ijet.v17i05.25691.
Yu, H., & Hu, J. (2022b). A multilevel regression analysis of computer-mediated communication in synchronous and asynchronous contexts and digital reading achievement in Japanese students. Interactive Learning Environments. Advance online publication. https://doi.org/10.1080/10494820.2022.2066136
Yu, J., Zhou, X., Yang, X., & Hu, J. (2022). Mobile-assisted or paper-based? The influence of the reading medium on the reading comprehension of English as a foreign language. Computer Assisted Language Learning, 35(1–2), 217–245. https://doi.org/10.1080/09588221.2021.2012200.
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This research was supported by the National Social Science Fund of China, China, “Construction and Research on the Multidimensional Evaluation of the Database of Chinese Second Language Students’ Reading Literacy” (Grant number: 21BYY024).
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Hu, J., Yu, H. Impact of extracurricular synchronous and asynchronous computer-mediated communication between students and teachers on digital reading performance: Evidence from 53 countries/regions. Educ Inf Technol 28, 1559–1586 (2023). https://doi.org/10.1007/s10639-022-11223-0
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DOI: https://doi.org/10.1007/s10639-022-11223-0