Résumés
Abstract
This meta-analysis examines the impact of technology in statistics learning, comparing experimental and control groups across 34 studies, resulting in 55 effect sizes. The random effects model revealed a significant standardized mean difference (gRE = 0.50, 95% CI [0.35, 0.64], p < 0.01), indicating a positive effect of using technology in statistics courses. Heterogeneity was high (I² = 94.3%), and publication bias was initially detected; however, it was addressed by removing 21 outlier studies. The analysis revealed no significant differences based on country; however, technology type had a significant effect. These findings suggest improved student outcomes, warranting further investigation.
Keywords:
- Statistics Education,
- Technology,
- Meta Analysis
Parties annexes
Bibliography
- Alam, A., & Mohanty, A. (2023). Educational technology: Exploring the convergence of technology and pedagogy through mobility, interactivity, AI, and learning tools. Cogent Engineering, 10(2), 2283282. https://doi.org/10.1080/23311916.2023.2283282
- Alyoussef, I. Y. (2023). Acceptance of e-learning in higher education: The role of task-technology fit with the information systems success model. Heliyon, 9(3), e13751. https://doi.org/10.1016/j.heliyon.2023.e13751
- An, Y., Kaplan-Rakowski, R., Yang, J., Conan, J., Kinard, W., & Daughrity, L. (2021). Examining K-12 teachers’ feelings, experiences, and perspectives regarding online teaching during the early stage of the COVID-19 pandemic. Educational Technology Research and Development, 69(5), 2589–2613. https://doi.org/10.1007/s11423-021-10008-5
- Baujat, B., Mahé, C., Pignon, J., & Hill, C. (2002). A graphical method for exploring heterogeneity in meta‐analyses: Application to a meta‐analysis of 65 trials. Statistics in Medicine, 21(18), 2641–2652. https://doi.org/10.1002/sim.1221
- Borenstein, M. (2023). How to understand and report heterogeneity in a meta-analysis: The difference between I-squared and prediction intervals. Integrative Medicine Research, 12(4), 101014. https://doi.org/10.1016/j.imr.2023.101014
- Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to meta-analysis. John Wiley & Sons.
- Boutron, I., Page, M. J., Higgins, J. P., Altman, D. G., Lundh, A., Hróbjartsson, A., & on behalf of the Cochrane Bias Methods Group. (2019). Considering bias and conflicts of interest among the included studies. In J. P. T. Higgins, J. Thomas, J. Chandler, M. Cumpston, T. Li, M. J. Page, & V. A. Welch (Eds.), Cochrane handbook for systematic reviews of interventions (1st ed., pp. 177–204). Wiley. https://doi.org/10.1002/9781119536604.ch7
- Büscher, C. (2022). Design principles for developing statistical literacy in middle schools. Statistics Education Research Journal, 21(1), 10. https://doi.org/10.52041/serj.v21i1.80
- Crettaz Von Roten, F., & De Roten, Y. (2023). Undergraduate sport sciences students’ attitudes towards statistics: A gender perspective. Journal of Hospitality, Leisure, Sport & Tourism Education, 33, 100452. https://doi.org/10.1016/j.jhlste.2023.100452
- Dani, A., & Al Quraan, E. (2023). Investigating research students’ perceptions about statistics and its impact on their choice of research approach. Heliyon, 9(10), e20423. https://doi.org/10.1016/j.heliyon.2023.e20423
- Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315(7109), 629–634. https://doi.org/10.1136/bmj.315.7109.629
- Emmi̇Oğlu, E., & Capa-Aydin, Y. (2012). Attitudes and achievement in statistics: A meta analysis study. Statistics Education Research Journal, 11(2), 95–102. https://doi.org/10.52041/serj.v11i2.332
- Farmus, L., Cribbie, R. A., & Rotondi, M. A. (2020). The flipped classroom in introductory statistics: Early evidence from a systematic review and meta-analysis. Journal of Statistics Education, 28(3), 316–325. https://doi.org/10.1080/10691898.2020.1834475
- Fragkos, K. C., Tsagris, M., & Frangos, C. C. (2014). Publication bias in meta-analysis: Confidence intervals for Rosenthal’s fail-safe number. International Scholarly Research Notices, 2014, 1–17. https://doi.org/10.1155/2014/825383
- Friedrich, S., Antes, G., Behr, S., Binder, H., Brannath, W., Dumpert, F., Ickstadt, K., Kestler, H. A., Lederer, J., Leitgöb, H., Pauly, M., Steland, A., Wilhelm, A., & Friede, T. (2022). Is there a role for statistics in artificial intelligence? Advances in Data Analysis and Classification, 16(4), 823–846. https://doi.org/10.1007/s11634-021-00455-6
- George, B. J., & Leon, J. (2023). Making the switch: Experiences and results from converting a biostatistics course to flipped and online formats for public health students. Journal of Statistics and Data Science Education, 31(1), 91–101. https://doi.org/
- 1080/26939169.2022.2046522
- Griffith, J. C., Faulconer, E. K., & McMasters, B. L. (2021). The relationship between learning mode and student performance in an undergraduate elementary statistics course in the United States. The International Review of Research in Open and Distributed Learning, 22(1), 166–179. https://doi.org/10.19173/irrodl.v22i1.5033
- Guido Schwarzer. (2023). General package for meta analysis. https://cran.r-project.org/web/packages/meta/meta.pdf
- Gundlach, E., Richards, K. A. R., Nelson, D., & Levesque-Bristol, C. (2015). A comparison of student attitudes, statistical reasoning, performance, and perceptions for web-augmented traditional, fully online, and flipped sections of a statistical literacy class. Journal of Statistics Education, 23(1), 3. https://doi.org/10.1080/10691898.2015.11889723
- Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3, 275–285. https://doi.org/10.1016/j.susoc.2022.05.004
- Hartawan, I. G. N. Y., & Suryawan, I. P. P. (2022). Implementasi bahan ajar berbasis masalah kontekstual berbantuan software statistika dalam meningkatkan hasil belajar. Jurnal Pendidikan Matematika Undiksha, 13(1), 74–80. https://doi.org/10.23887/
- jjpm.v13i1.47073
- Hedges, L. V. (1981). Distribution theory for Glass’s estimator of effect size and related estimators. Journal of Educational Statistics, 6(2), 107. https://doi.org/10.2307/1164588
- Higgins, J. P. T., & Thompson, S. G. (2002). Quantifying heterogeneity in a meta‐analysis. Statistics in Medicine, 21(11), 1539–1558. https://doi.org/10.1002/sim.1186
- Hoffman, H. J., & Elmi, A. F. (2021). Comparing student performance in a graduate-level introductory biostatistics course using an online versus a traditional in-person learning environment. Journal of Statistics and Data Science Education, 29(1), 105–114. https://doi.org/10.1080/10691898.2020.1841592
- Holm, L. B., Rognes, A., & Dahl, F. A. (2022). The FLIPPED STEP study: A randomized controlled trial of flipped vs. traditional classroom teaching in a university-level statistics and epidemiology course. International Journal of Educational Research Open, 3, 100197. https://doi.org/10.1016/j.ijedro.2022.100197
- Immekus, J. C. (2019). Flipping statistics courses in graduate education: Integration of cognitive psychology and technology. Journal of Statistics Education, 27(2), 79–89. https://doi.org/10.1080/10691898.2019.1629852
- Jian, G., Liping, Z., Jiangjie, S., Yanan, D., & Min, Y. (2021). Research on the application of blended teaching in probability theory and mathematical statistics based on MOOC + SPOC + flipped classroom. Education Journal, 10(6), 226. https://doi.org/10.11648/j.edu.20211006.13
- Kalaian, S. A., & Kasim, R. M. (2014). A meta-analytic review of studies of the effectiveness of small-group learning methods on statistics achievement. Journal of Statistics Education, 22(1), 2. https://doi.org/10.1080/10691898.2014.11889691
- Khoshnoodifar, M. (2023). Effectiveness of gamification in enhancing learning and attitudes: A study of statistics education for health school students. Journal of Advances in Medical Education & Professionalism, 11(4).
- Koparan, T. (2019). Examination of the dynamic software-supported learning environment in data analysis. International Journal of Mathematical Education in Science and Technology, 50(2), 277–291. https://doi.org/10.1080/0020739X.2018.1494861
- Kriswanto, E. S., Pambudi, A. F., Retnawati, H., Siswantoyo, Arifin, S., & Putranta, H. (2021). Effect of leg length on running speed of sports and health sciences students in Indonesia: A meta-analysis study. Journal of Physical Education and Sport, 21(5), 2697-2705.
- Kühberger, A., Fritz, A., & Scherndl, T. (2014). Publication bias in psychology: A diagnosis Based on the correlation between effect size and sample size. PLoS ONE, 9(9), e105825. https://doi.org/10.1371/journal.pone.0105825
- Legaki, N.-Z., Xi, N., Hamari, J., Karpouzis, K., & Assimakopoulos, V. (2020). The effect of challenge-based gamification on learning: An experiment in the context of statistics education. International Journal of Human-Computer Studies, 144, 102496. https://doi.org/10.1016/j.ijhcs.2020.102496
- Liao, C.-H., & Wu, J.-Y. (2023). Learning analytics on video-viewing engagement in a flipped statistics course: Relating external video-viewing patterns to internal motivational dynamics and performance. Computers & Education, 197, 104754. https://doi.org/10.1016/j.compedu.2023.104754
- Liu, F., Vadivel, B., Rezvani, E., & Namaziandost, E. (2021). Using games to promote English as a foreign language learners’ willingness to communicate: Potential effects and teachers’ attitude in focus. Frontiers in Psychology, 12, 762447. https://doi.org/10.3389/fpsyg.2021.762447
- Liu, K. Z. (2023). FS-Net: Frequency statistical network for temporal knowledge graph reasoning. Ruan Jian Xue Bao/Journal of Software, 34(10). https://doi.org/10.13328/j.cnki.jos.006885
- Loux, T. M., Varner, S. E., & VanNatta, M. (2016). Flipping an introductory biostatistics course: A case study of student attitudes and confidence. Journal of Statistics Education, 24(1), 1–7. https://doi.org/10.1080/10691898.2016.1158017
- McCulloch, R. S. (2017). Learning outcomes in a laboratory environment vs. classroom for statistics instruction: An alternative approach using statistical software. International Journal of Higher Education, 6(5), 131. https://doi.org/10.5430/ijhe.v6n5p131
- Naufal Dzakwan, Murtinugraha, R. E., & Arthur, R. (2021). Efektivitas penggunaan e-modul pada mata kuliah statistika di program studi pendidikan teknik bangunan fakultas teknik Universitas Negeri Jakarta. Risenologi, 6(1b), 70–77. https://doi.org/10.47028/j.risenologi.2021.61b.249
- Nielsen, P. L., Bean, N. W., & Larsen, R. A. A. (2018). The impact of a flipped classroom model of learning on a large undergraduate statistics class. Statistics Education Research Journal, 17(1), 121–140. https://doi.org/10.52041/serj.v17i1.179
- Peterson, D. J. (2016). The flipped classroom improves student achievement and course satisfaction in a statistics course: A quasi-experimental study. Teaching of Psychology, 43(1), 10–15. https://doi.org/10.1177/0098628315620063
- Rakes, C. R., Ronau, R. N., Bush, S. B., Driskell, S. O., Niess, M. L., & Pugalee, D. K. (2020). Mathematics achievement and orientation: A systematic review and meta-analysis of education technology. Educational Research Review, 31, 100337. https://doi.org/10.1016/j.edurev.2020.100337
- Retnawati, H., Apino, E., Djidu, H., & Anazifa, R. D. (2018). Pengantar analisis meta (edisi 1). Parama Publishing.
- Reyneke, F., Fletcher, L., & Harding, A. (2021). Enhancing a flipped statistics first year course by using QT-clickers. Journal of Statistics and Data Science Education, 29(1), 71–83. https://doi.org/10.1080/10691898.2021.1895694
- Schmid, R. F., Borokhovski, E., Bernard, R. M., Pickup, D. I., & Abrami, P. C. (2023). A meta-analysis of online learning, blended learning, the flipped classroom and classroom instruction for pre-service and in-service teachers. Computers and Education Open, 5, 100142. https://doi.org/10.1016/j.caeo.2023.100142
- Soodtoetong, N., & Rattanasiriwongwut, M. (2022). Educational transformation with virtual classroom: Integrated between TTF and social motivation. TEM Journal, 439–445. https://doi.org/10.18421/TEM111-56
- Tishkovskaya, S., & Lancaster, G. A. (2012). Statistical education in the 21st century: A review of challenges, teaching innovations and strategies for reform. Journal of Statistics Education, 20(2), 4. https://doi.org/10.1080/10691898.2012.11889641
- Van Alten, D. C. D., Phielix, C., Janssen, J., & Kester, L. (2019). Effects of flipping the classroom on learning outcomes and satisfaction: A meta-analysis. Educational Research Review, 28, 100281. https://doi.org/10.1016/j.edurev.2019.05.003
- Wen, X., & Walters, S. M. (2022). The impact of technology on students’ writing performances in elementary classrooms: A meta-analysis. Computers and Education Open, 3, 100082. https://doi.org/10.1016/j.caeo.2022.100082
- Yang, S. C., & Chen, Y.-J. (2007). Technology-enhanced language learning: A case study. Computers in Human Behavior, 23(1), 860–879. https://doi.org/10.1016/j.chb.2006.02.015